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Mitochondrial DNA (mtDNA) has an important, yet often overlooked, role in health and disease. Constraint models quantify the removal of deleterious variation from the population by selection, representing a powerful tool for identifying genetic variation underlying human phenotypes1–4. However, a constraint model for the mtDNA has not been developed, due to its unique features. Here we describe the development of a mitochondrial constraint model and its application to the Genome Aggregation Database (gnomAD), a large-scale population dataset reporting mtDNA variation across 56,434 humans5. Our results demonstrate strong depletion of expected variation, suggesting most deleterious mtDNA variants remain undiscovered. To aid their identification, we compute constraint metrics for every mitochondrial protein, tRNA, and rRNA gene, revealing a spectrum of intolerance to variation. We characterize the most constrained regions within genes via regional constraint, and positions across the entire mtDNA via local constraint, showing their enrichment in pathogenic variation and functionally critical sites, including topological clustering in 3D protein and RNA structures. Notably, we identify constraint at often overlooked sites, such as rRNAs and non-coding regions. Lastly, we demonstrate how these metrics can improve the discovery of mtDNA variation underlying rare and common human phenotypes.

SummaryMitochondria are involved in energetic, biosynthetic, and homeostatic processes in eukaryotic cells. Mitochondria carry their own circular genome and disruption of the quantity or quality of mitochondrial genome is associated with various aging-related diseases1–3. Unlike the nuclear genome, mitochondrial DNA (mtDNA) can be present at 1,000s to 10,000s copies in somatic cells and variants may exist in a state of heteroplasmy, where only a fraction of the DNA molecules harbor a particular variant. We used MitoHPC, a bioinformatics pipeline, to accurately quantify mtDNA heteroplasmy from whole genome sequencing data in 194,871 participants in the UK Biobank. We found that the presence of heteroplasmy is associated with an increased risk of all-cause mortality (adjusted hazard ratio [aHR] 1.50-fold; 95% confidence interval [CI] 1.14, 1.98, when comparing participants with 4 or more heteroplasmies to those without any heteroplasmy). In addition, we functionally characterized mtDNA single nucleotide variants (SNVs) using a novel constraint-based score, Mitochondrial local constraint (MLC) score sum (MSS), which demonstrated that SNVs at highly constrained sites were strongly associated with all-cause mortality (aHR for a 1-unit increase in MSS 1.28; 95% CI 1.20, 1.37) and cancer-related mortality (aHR 1.36; 95% CI 1.24,1.49), particularly lung and breast cancers, lymphoma, and leukemia. MSS was also associated with prevalence and incidence of lung cancer, lymphoma, and leukemia. Moreover, among individuals with prevalent leukemia, high MSS was strongly associated with leukemia mortality (adjusted HR 4.03; 95% CI 1.34, 12.11). These results indicate that mitochondria may have a functional role in certain cancers and mitochondrial heteroplasmic SNVs have the potential to serve as a prognostic markers for cancer incidence and outcome, especially for leukemia.

Mitochondrial DNA copy number (mtDNA-CN) is a proxy for mitochondrial function and has been of increasing interest to the mitochondrial research community. There are a number of ways to measure mtDNA-CN, ranging from qPCR to whole genome sequencing [1]. A recent article in the Journal of Molecular Diagnostics [2] described a novel method for measuring mtDNA-CN that is both inexpensive and reproducible. After adapting the assay for use in our lab, we have found it to be reproducible and well-correlated with mtDNA-CN derived from whole genome sequencing. However, certain individuals show poor concordance between the two measures, particularly individuals with qPCR mtDNA-CN measurements >3 standard deviations below the sample mean, which corresponds to roughly 1% of assayed individuals (Figure 1). After examining whole genome sequencing data, this seems to be due to specific polymorphisms within the D-loop primer region, at positions MT 338, 340, 452, 457, 458, 460, 461, 466, and 467. All individuals with a variant in at least one of these positions have non-concordant mtDNA-CN measurements. Meanwhile, variants observed at other positions within the primer region do not appear to cause dropout. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/463983v1_fig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@134ca51org.highwire.dtl.DTLVardef@ce9196org.highwire.dtl.DTLVardef@1b82af6org.highwire.dtl.DTLVardef@c9701_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Discrepancy between the monochrome multiplex qPCR mtDNA-CN and the whole genome sequencing mtDNA-CN for 1,732 distinct individuals. Data are centered at 0 and scaled so that the standard deviation = 1. The dotted red line represents 3 standard deviations beneath the sample mean. Individuals in the U, L1, L4, and T haplogroups have a disproportionately higher risk of discordant measures between the two assays. C_FIG

Summary Human bone marrow stromal cells, or mesenchymal stem cells (BM-MSCs), need expansion prior to use as cell-based therapies in immunological and tissue repair applications. Aging and expansion of BM-MSCs induce epigenetic changes that can impact therapeutic outcomes. By applying sequencing-based methods, we reveal that the breadth of DNA methylation dynamics associated with aging and expansion is greater than previously reported. Methylation changes are enriched at known distal transcription factor binding sites such as enhancer elements, instead of CpG-rich regions, and are associated with changes in gene expression. From this, we constructed hypo- and hypermethylation-specific regulatory networks, including a sub-network of BM-MSC master regulators and their predicted target genes, and identified putatively disrupted signaling pathways. Our genome-wide analyses provide a broader overview of age- and expansion-induced DNA methylation changes and a better understanding of the extent to which these changes alter gene expression and functionality of human BM-MSCs., Graphical Abstract, Highlights • Global DNA methylome analysis for human bone marrow mesenchymal stromal cells • Young versus aged adult donors compared at early and late passages • Differential methylation is enriched at distal transcription factor binding sites • These TFBSs are frequently found within BM-MSC enhancers indicated by H3K4me1, Bone marrow MSCs are of great therapeutic interest. Hawkins and colleagues show that sequencing-based approaches to study differential DNA methylation induced by donor age or cell passage reveal more extensive changes than previous array-based studies. These changes are enriched at known transcription factor binding sites within BM-MSC enhancer elements and can be associated with changes in gene expression.

Early embryonic development is characterized by a dynamic epigenome. Some of the most drastic changes occur as the mammalian embryo transitions from the free-floating, preimplantation blastocyst to the early embryo embedded in the uterus. Efforts to understand early embryonic molecular phenotypes have driven the derivation of mammalian embryonic stem cells that represent the pre- and postimplantation embryo, termed naive and primed embryonic stem cells. Here, we describe in detail mouse and human embryonic stem cell derivation as it pertains to pre- and postimplantation development. We look at the epigenetic research conducted in these systems and what we have learned to date. We highlight whenever possible in vivo embryo studies as a comparison with the in vitro embryonic stem cell studies. Where data are lacking, we describe what is currently known. Altogether, we hope to focus attention on the research that has led to major discoveries in naive and primed pluripotent stem cells.

Oocyte maturation is a coordinated process that is tightly linked to reproductive potential. A better understanding of gene regulation during human oocyte maturation will not only answer an important question in biology, but also facilitate the development of in vitro maturation technology as a fertility treatment. We generated single-cell transcriptome and used our previously published single-cell methylome data from human oocytes at different maturation stages to investigate how genes are regulated during oocyte maturation, focusing on the potential regulatory role of non-CpG methylation. DNMT3B, a gene encoding a key non-CpG methylation enzyme, is one of the 1,077 genes upregulated in mature oocytes, which may be at least partially responsible for the increased non-CpG methylation as oocytes mature. Non-CpG differentially methylated regions (DMRs) between mature and immature oocytes have multiple binding motifs for transcription factors, some of which bind with DNMT3B and may be important regulators of oocyte maturation through non-CpG methylation. Over 98% of non-CpG DMRs locate in transposable elements, and these DMRs are correlated with expression changes of the nearby genes. Taken together, this data indicates that global non-CpG hypermethylation during oocyte maturation may play an active role in gene expression regulation, potentially through the interaction with transcription factors.

Oocyte maturation is a coordinated process that is tightly linked to reproductive potential. A better understanding of gene regulation during human oocyte maturation will not only answer an important question in biology, but also facilitate the development of in vitro maturation technology as a fertility treatment. We generated single-cell transcriptome and use previously published single-cell methylome data from human oocytes at different maturation stages to investigate how genes are regulated during oocyte maturation, focusing on the potential regulatory role of non-CG methylation. DNMT3B, a gene encoding a key non-CG methylation enzyme, is one of the 1000 genes upregulated in mature oocytes, which may be at least partially responsible for the increased non-CG methylation as oocytes mature. Non-CG differentially methylated regions (DMRs) between mature and immature oocytes have multiple binding motifs for transcription factors, some of which bind with DNMT3B and may be important regulators of oocyte maturation through non-CG methylation. Over 98% of non-CG DMRs locate in transposable elements, and these DMRs are correlated with expression changes of the nearby genes. Taken together, this data indicates that global non-CG hypermethylation during oocyte maturation may play an active role in gene expression regulation, potentially through the interaction with transcription factors.

Assisted reproductive technologies are known to alter the developmental environment of gametes and early embryos during the most dynamic period of establishing the epigenome. This may result in the introduction of errors during active DNA methylation reprogramming. Controlled ovarian hyperstimulation, or superovulation, is a ubiquitously used intervention which has been demonstrated to alter the methylation of certain imprinted genes. The objective of this study was to investigate whether ovarian hyperstimulation results in genome-wide DNA methylation changes in mouse early embryos. Ovarian hyperstimulation was induced by treating mice with either low doses (5 IU) or high doses (10 IU) of PMSG and hCG. Natural mating (NM) control mice received no treatment. Zygotes and 8-cell embryos were collected from each group and DNA methylomes were generated by whole-genome bisulfite sequencing. In the NM group, mean CpG methylation levels slightly decreased from zygote to 8-cell stage, whereas a large decrease in mean CpG methylation level was observed in both superovulated groups. A separate analysis of the mean CpG methylation levels within each developmental stage confirmed that significant genome-wide erasure of CpG methylation from the zygote to 8-cell stage only occurred in the superovulation groups. Our results suggest that superovulation alters the genome-wide DNA methylation erasure process in mouse early pre-implantation embryos. It is not clear whether these changes are transient or persistent. Further studies are ongoing to investigate the impact of ovarian hyperstimulation on DNA methylation re-establishment in later stages of embryo development.

To reveal how cells exit human pluripotency, we designed a CRISPR-Cas9 screen exploiting the metabolic and epigenetic differences between naïve and primed pluripotent cells. We identify the tumor suppressor, Folliculin(FLCN) as a critical gene required for the exit from human pluripotency. Here we show that FLCN Knock-out (KO) hESCs maintain the naïve pluripotent state but cannot exit the state since the critical transcription factor TFE3 remains active in the nucleus. TFE3 targets up-regulated in FLCN KO exit assay are members of Wnt pathway and ESRRB. Treatment of FLCN KO hESC with a Wnt inhibitor, but not ESRRB/FLCN double mutant, rescues the cells, allowing the exit from the naïve state. Using co-immunoprecipitation and mass spectrometry analysis we identify unique FLCN binding partners. The interactions of FLCN with components of the mTOR pathway (mTORC1 and mTORC2) reveal a mechanism of FLCN function during exit from naïve pluripotency., The pathways involved in exit from pluripotency in human embryonic stem cells are poorly understood. Here, the authors performed a CRISPR-based screen to identify genes that promote exit from naïve pluripotency and find a role for folliculin (FLCN) by regulating the mTOR and Wnt pathways.

For nearly a century developmental biologists have recognized that cells from embryos can differ in their potential to differentiate into distinct cell types. Recently, it has been recognized that embryonic stem cells derived from both mice and humans exhibit two stable yet epigenetically distinct states of pluripotency: naive and primed. We now show that nicotinamide N-methyltransferase (NNMT) and the metabolic state regulate pluripotency in human embryonic stem cells (hESCs). Specifically, in naive hESCs, NNMT and its enzymatic product 1-methylnicotinamide are highly upregulated, and NNMT is required for low S-adenosyl methionine (SAM) levels and the H3K27me3 repressive state. NNMT consumes SAM in naive cells, making it unavailable for histone methylation that represses Wnt and activates the HIF pathway in primed hESCs. These data support the hypothesis that the metabolome regulates the epigenetic landscape of the earliest steps in human development.

The small phenolic compound salicylic acid (SA) plays a critical role in plant defense against broad-spectrum of pathogens. The phosphate transporter gene PHT4;1 was previously shown to affect SA-mediated defense and its expression is regulated by the circadian clock. To further understand how PHT4;1 affects SA accumulation, here we analyzed the genetic interactions between the gain-of-function mutant pht4;1-1 and several known SA mutants, including sid2-1, ald1-1, eds5-3, and pad4-1. The genetic analysis was conducted in the acd6-1 background since the change of acd6-1 dwarfism can be used as a convenient readout for the change of defense levels caused by impairments in some SA genes. We found that compared with the corresponding double mutants, the triple mutants acd6-1pht4;1-1ald1-1, acd6-1pht4;1-1eds5-3, and acd6-1pht4;1-1pad4-1 accumulated lower levels of SA and PR1 transcripts, suggesting that PHT4;1 contributes to acd6-1-conferred defense phenotypes independently of these known SA regulators. Although some triple mutants had wild type (wt)-like levels of SA and PR1 transcripts, these plants were smaller than wt and displayed minor cell death, suggesting that additional regulatory pathways contribute to acd6-1-conferred dwarfism and cell death. Our data further showed that circadian expression of PHT4;1 was dependent on CIRCADIAN CLOCK ASSOCIATED 1 (CCA1), a central oscillator component of Arabidopsis circadian clock. Recombinant CCA1 protein was demonstrated to bind to the PHT4;1 promoter in electrophoretic mobility shift assays, suggesting a direct transcriptional regulation of PHT4;1 by CCA1. Together these results indicate that PHT4;1 is a SA regulator acting independently of several known SA genes and they also implicate a role of the circadian clock mediated by CCA1 in regulating phosphate transport and/or innate immunity in Arabidopsis.

The Arabidopsis accelerated cell death 6-1 (acd6-1) mutant shows constitutive defense, cell death, and extreme dwarf phenotypes. In a screen for acd6-1 suppressors, we identified a mutant that was disrupted by a T-DNA in the PHOSPHATE TRANSPORTER 4;1 (PHT4;1) gene. The suppressor mutant pht4;1-1 is dominant, expresses truncated PHT4;1 transcripts, and is more susceptible to virulent Pseudomonas syringae strains but not to several avirulent strains. Treatment with a salicylic acid (SA) agonist induced a similar level of resistance in Col-0 and pht4;1-1, suggesting that PHT4;1 acts upstream of the SA pathway. Genetic analysis further indicates that PHT4;1 contributes to SID2-dependent and -independent pathways. Transgenic expression of the DNA fragment containing the PHT4;1-1 region or the full-length PHT4;1 gene in wild-type conferred enhanced susceptibility to Pseudomonas infection. Interestingly, expression of PHT4;1 is regulated by the circadian clock. Together, these data suggest that the phosphate transporter PHT4;1 is critical for basal defense and also implicate a potential role of the circadian clock in regulating innate immunity of Arabidopsis.

Ovarian cancer is the fifth leading cause of cancer mortality among women in the United States. Despite aggressive surgery and chemotherapy, most patients relapse and develop drug-resistant tumors, leading to the The epigenome provides the structural framework for cell-type specific gene regulation. Chromatin modifications that uniquely mark gene regulatory elements, like promoters and enhancers, are easily identified throughout the genome using ChIP-seq. ChIP-seq performed in pluripotent stem cells has revealed many epigenetic features that distinguish them from differentiated cells. In an effort to better understand CSC gene regulatory networks, we are generating comprehensive transcriptomic maps and globally identifying enhancers marked by histone 3, lysine 4 monomethylation (via RNAseq and H3K4me1 ChIP-seq respectively) in OvCSCs and their daughter tumor cells. We are also comparing OvCSCs to previously generated data in human embryonic stem cells (hESCs) to identify shared stemness traits. OvCSCs were acquired from patient biopsies and detailed characterization identified a CD133+ CSC population within the tumor. We are using a mouse xenograft model to expand tumors in vivo. Harvested tumors are depleted of blood lineage cells and CD133+ cells (CSCs) are isolated from the remaining cells in the tumor. Our analysis of RNA-seq and enhancer maps have revealed OvCSC signatures that are absent in tumor cells but present in embryonic stem cells. Many important embryonic stem cell transcription factors are expressed in OvCSCs and have almost identical chromatin enhancer profiles. We identified over 7000 H1 hESC enhancers that have at least 95% overlap with OvCSC enhancers implying a shared regulatory network in these cell types. Motif analysis of nucleosome-free regions within enhancers reveals enrichment for many ESC transcription factors that are also expressed in OvCSCs. Our integrative analysis indicates that OvCSCs share common features of the ESC regulatory network and is beginning to provide novel insight on why CSCs have stem cell properties. We are continuing to build maps for additional histone modifications and genome-wide DNA methylation in OvCSCs to gain a comprehensive view of how the epigenome regulates the cancer stem cell state. Citation Format: Stephanie L. Battle, Antti Larjo, Joling Liao, Harri Lähdesmäki, Andre Lieber, R. David Hawkins. Epigenomic characterization of gene regulatory networks in human ovarian cancer stem cells [abstract]. In: Proceedings of the 10th Biennial Ovarian Cancer Research Symposium; Sep 8-9, 2014; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(16 Suppl):Abstract nr AS04.

Background ChIP-seq is highly utilized for mapping histone modifications that are informative about gene regulation and genome annotations. For example, applying ChIP-seq to histone modifications such as H3K4me1 has facilitated generating epigenomic maps of putative enhancers. This powerful technology, however, is limited in its application by the large number of cells required. ChIP-seq involves extensive manipulation of sample material and multiple reactions with limited quality control at each step, therefore, scaling down the number of cells required has proven challenging. Recently, several methods have been proposed to overcome this limit but most of these methods require extensive optimization to tailor the protocol to the specific antibody used or number of cells being profiled. Results Here we describe a robust, yet facile method, which we named carrier ChIP-seq (cChIP-seq), for use on limited cell amounts. cChIP-seq employs a DNA-free histone carrier in order to maintain the working ChIP reaction scale, removing the need to tailor reactions to specific amounts of cells or histone modifications to be assayed. We have applied our method to three different histone modifications, H3K4me3, H3K4me1 and H3K27me3 in the K562 cell line, and H3K4me1 in H1 hESCs. We successfully obtained epigenomic maps for these histone modifications starting with as few as 10,000 cells. We compared cChIP-seq data to data generated as part of the ENCODE project. ENCODE data are the reference standard in the field and have been generated starting from tens of million of cells. Our results show that cChIP-seq successfully recapitulates bulk data. Furthermore, we showed that the differences observed between small-scale ChIP-seq data and ENCODE data are largely to be due to lab-to-lab variability rather than operating on a reduced scale. Conclusions Data generated using cChIP-seq are equivalent to reference epigenomic maps from three orders of magnitude more cells. Our method offers a robust and straightforward approach to scale down ChIP-seq to as low as 10,000 cells. The underlying principle of our strategy makes it suitable for being applied to a vast range of chromatin modifications without requiring expensive optimization. Furthermore, our strategy of a DNA-free carrier can be adapted to most ChIP-seq protocols. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-2285-7) contains supplementary material, which is available to authorized users.

Background:Discovering patient subtypes and molecular drivers of a subtype are difficult and driving problems underlying most modern disease expression studies collected across patient populations. Expression patterns conserved across multiple expression datasets from independent disease studies are likely to represent important molecular events underlying the disease.Methods:We present the INSPIRE (INferring Shared modules from multiPle gene expREssion datasets) method to infer highly coherent and robust modules of co-expressed genes and the dependencies among the modules from multiple expression datasets. Focusing on inferring modules and their dependencies conserved across multiple expression datasets is important for several reasons. First, using multiple datasets will increase the power to detect robust and relevant patterns (modules and dependencies among modules). Second, INSPIRE enables the use of multiple datasets that contain different sets of genes due to, e.g., the difference in microarray platforms. Many methods designed for expression data analysis cannot integrate multiple datasets with variable discrepancy to infer a single combined model, whereas INSPIRE can naturally model the dependencies among the modules even when a large proportion of genes are not observed on a certain platform.Results:We evaluated INSPIRE on synthetically generated datasets with known underlying network structure among modules, and gene expression datasets from multiple ovarian cancer studies. We show that the model learned by INSPIRE can explain unseen data better and can reveal prior knowledge on gene functions more accurately than alternative methods. We demonstrate that applying INSPIRE to nine ovarian cancer datasets leads to the identification of a new marker and potential molecular driver of tumor-associated stroma - HOPX. We also demonstrate that the HOPXmodule strongly overlaps with the genes defining the mesenchymal patient subtype identified in The Cancer Genome Atlas (TCGA) ovarian cancer data. We provide evidence for a previously unknown molecular basis of tumor resectability efficacy involving tumor-associated mesenchymal stem cells represented by HOPX.Conclusions:INSPIRE extracts a low-dimensional description from multiple gene expression data, which consists of modules and their dependencies. The discovery of a new tumor-associated stroma marker, HOPX, and its module suggests a previously unknown mechanism underlying tumor-associated stroma.