Cooperative Binding of Transcription Factors Orchestrates Reprogramming.

Oct4, Sox2, Klf4, and cMyc (OSKM) reprogram somatic cells to pluripotency. To gain a mechanistic understanding of their function, we mapped OSKM-binding, stage-specific transcription factors (TFs), and chromatin states in discrete reprogramming stages and performed loss- and gain-of-function experiments. We found that OSK predominantly bind active somatic enhancers early in reprogramming and immediately initiate their inactivation genome-wide by inducing the redistribution of somatic TFs away from somatic enhancers to sites elsewhere engaged by OSK, recruiting Hdac1, and repressing the somatic TF Fra1. Pluripotency enhancer selection is a stepwise process that also begins early in reprogramming through collaborative binding of OSK at sites with high OSK-motif density. Most pluripotency enhancers are selected later in the process and require OS and other pluripotency TFs. Somatic and pluripotency TFs modulate reprogramming efficiency when overexpressed by altering OSK targeting, somatic-enhancer inactivation, and pluripotency enhancer selection. Together, our data indicate that collaborative interactions among OSK and with stage-specific TFs direct both somatic-enhancer inactivation and pluripotency-enhancer selection to drive reprogramming.

A framework for group-wise summarization and comparison of chromatin state annotations.

MOTIVATION: Genome-wide maps of epigenetic modifications are powerful resources for non-coding genome annotation. Maps of multiple epigenetics marks have been integrated into cell or tissue type-specific chromatin state annotations for many cell or tissue types. With the increasing availability of multiple chromatin state maps for biologically similar samples, there is a need for methods that can effectively summarize the information about chromatin state annotations within groups of samples and identify differences across groups of samples at a high resolution. RESULTS: We developed CSREP, which takes as input chromatin state annotations for a group of samples. CSREP then probabilistically estimates the state at each genomic position and derives a representative chromatin state map for the group. CSREP uses an ensemble of multi-class logistic regression classifiers that predict the chromatin state assignment of each sample given the state maps from all other samples. The difference in CSREP's probability assignments for the two groups can be used to identify genomic locations with differential chromatin state assignments. Using groups of chromatin state maps of a diverse set of cell and tissue types, we demonstrate the advantages of using CSREP to summarize chromatin state maps and identify biologically relevant differences between groups at a high resolution. AVAILABILITY AND IMPLEMENTATION: The CSREP source code and generated data are available at http://github.com/ernstlab/csrep. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BS-Seeker2: a versatile aligning pipeline for bisulfite sequencing data.

BACKGROUND: DNA methylation is an important epigenetic modification involved in many biological processes. Bisulfite treatment coupled with high-throughput sequencing provides an effective approach for studying genome-wide DNA methylation at base resolution. Libraries such as whole genome bisulfite sequencing (WGBS) and reduced represented bisulfite sequencing (RRBS) are widely used for generating DNA methylomes, demanding efficient and versatile tools for aligning bisulfite sequencing data. RESULTS: We have developed BS-Seeker2, an updated version of BS Seeker, as a full pipeline for mapping bisulfite sequencing data and generating DNA methylomes. BS-Seeker2 improves mappability over existing aligners by using local alignment. It can also map reads from RRBS library by building special indexes with improved efficiency and accuracy. Moreover, BS-Seeker2 provides additional function for filtering out reads with incomplete bisulfite conversion, which is useful in minimizing the overestimation of DNA methylation levels. We also defined CGmap and ATCGmap file formats for full representations of DNA methylomes, as part of the outputs of BS-Seeker2 pipeline together with BAM and WIG files. CONCLUSIONS: Our evaluations on the performance show that BS-Seeker2 works efficiently and accurately for both WGBS data and RRBS data. BS-Seeker2 is freely available at http://pellegrini.mcdb.ucla.edu/BS_Seeker2/ and the Galaxy server.

Rare penetrant mutations confer severe risk of common diseases.

We examined 454,712 exomes for genes associated with a wide spectrum of complex traits and common diseases and observed that rare, penetrant mutations in genes implicated by genome-wide association studies confer ∼10-fold larger effects than common variants in the same genes. Consequently, an individual at the phenotypic extreme and at the greatest risk for severe, early-onset disease is better identified by a few rare penetrant variants than by the collective action of many common variants with weak effects. By combining rare variants across phenotype-associated genes into a unified genetic risk model, we demonstrate superior portability across diverse global populations compared to common variant polygenic risk scores, greatly improving the clinical utility of genetic-based risk prediction. One sentence summary: Rare variant polygenic risk scores identify individuals with outlier phenotypes in common human diseases and complex traits.

Rare penetrant mutations confer severe risk of common diseases.

We examined 454,712 exomes for genes associated with a wide spectrum of complex traits and common diseases and observed that rare, penetrant mutations in genes implicated by genome-wide association studies confer ~10-fold larger effects than common variants in the same genes. Consequently, an individual at the phenotypic extreme and at the greatest risk for severe, early-onset disease is better identified by a few rare penetrant variants than by the collective action of many common variants with weak effects. By combining rare variants across phenotype-associated genes into a unified genetic risk model, we demonstrate superior portability across diverse global populations compared with common-variant polygenic risk scores, greatly improving the clinical utility of genetic-based risk prediction.

The landscape of tolerated genetic variation in humans and primates.

Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole genome sequencing data for 809 individuals from 233 primate species, and identified 4.3 million common protein-altering variants with orthologs in human. We show that these variants can be inferred to have non-deleterious effects in human based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases. One Sentence Summary: Deep learning classifier trained on 4.3 million common primate missense variants predicts variant pathogenicity in humans.

The landscape of tolerated genetic variation in humans and primates.

Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole-genome sequencing data for 809 individuals from 233 primate species and identified 4.3 million common protein-altering variants with orthologs in humans. We show that these variants can be inferred to have nondeleterious effects in humans based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases.

ChromTime: modeling spatio-temporal dynamics of chromatin marks.

To model spatial changes of chromatin mark peaks over time we develop and apply ChromTime, a computational method that predicts peaks to be either expanding, contracting, or holding steady between time points. Predicted expanding and contracting peaks can mark regulatory regions associated with transcription factor binding and gene expression changes. Spatial dynamics of peaks provide information about gene expression changes beyond localized signal density changes. ChromTime detects asymmetric expansions and contractions, which for some marks associate with the direction of transcription. ChromTime facilitates the analysis of time course chromatin data in a range of biological systems.

Mapping molecular landmarks of human skeletal ontogeny and pluripotent stem cell-derived articular chondrocytes.

Tissue-specific gene expression defines cellular identity and function, but knowledge of early human development is limited, hampering application of cell-based therapies. Here we profiled 5 distinct cell types at a single fetal stage, as well as chondrocytes at 4 stages in vivo and 2 stages during in vitro differentiation. Network analysis delineated five tissue-specific gene modules; these modules and chromatin state analysis defined broad similarities in gene expression during cartilage specification and maturation in vitro and in vivo, including early expression and progressive silencing of muscle- and bone-specific genes. Finally, ontogenetic analysis of freshly isolated and pluripotent stem cell-derived articular chondrocytes identified that integrin alpha 4 defines 2 subsets of functionally and molecularly distinct chondrocytes characterized by their gene expression, osteochondral potential in vitro and proliferative signature in vivo. These analyses provide new insight into human musculoskeletal development and provide an essential comparative resource for disease modeling and regenerative medicine.

Systematic Epigenomic Analysis Reveals Chromatin States Associated with Melanoma Progression.

The extent and nature of epigenomic changes associated with melanoma progression is poorly understood. Through systematic epigenomic profiling of 35 epigenetic modifications and transcriptomic analysis, we define chromatin state changes associated with melanomagenesis by using a cell phenotypic model of non-tumorigenic and tumorigenic states. Computation of specific chromatin state transitions showed loss of histone acetylations and H3K4me2/3 on regulatory regions proximal to specific cancer-regulatory genes in important melanoma-driving cell signaling pathways. Importantly, such acetylation changes were also observed between benign nevi and malignant melanoma human tissues. Intriguingly, only a small fraction of chromatin state transitions correlated with expected changes in gene expression patterns. Restoration of acetylation levels on deacetylated loci by histone deacetylase (HDAC) inhibitors selectively blocked excessive proliferation in tumorigenic cells and human melanoma cells, suggesting functional roles of observed chromatin state transitions in driving hyperproliferative phenotype. Through these results, we define functionally relevant chromatin states associated with melanoma progression.

Dual Roles of RNF2 in Melanoma Progression.

UNLABELLED: Epigenetic regulators have emerged as critical factors governing the biology of cancer. Here, in the context of melanoma, we show that RNF2 is prognostic, exhibiting progression-correlated expression in human melanocytic neoplasms. Through a series of complementary gain-of-function and loss-of-function studies in mouse and human systems, we establish that RNF2 is oncogenic and prometastatic. Mechanistically, RNF2-mediated invasive behavior is dependent on its ability to monoubiquitinate H2AK119 at the promoter of LTBP2, resulting in silencing of this negative regulator of TGFß signaling. In contrast, RNF2's oncogenic activity does not require its catalytic activity nor does it derive from its canonical gene repression function. Instead, RNF2 drives proliferation through direct transcriptional upregulation of the cell-cycle regulator CCND2. We further show that MEK1-mediated phosphorylation of RNF2 promotes recruitment of activating histone modifiers UTX and p300 to a subset of poised promoters, which activates gene expression. In summary, RNF2 regulates distinct biologic processes in the genesis and progression of melanoma via different molecular mechanisms. SIGNIFICANCE: The role of epigenetic regulators in cancer progression is being increasingly appreciated. We show novel roles for RNF2 in melanoma tumorigenesis and metastasis, albeit via different mechanisms. Our findings support the notion that epigenetic regulators, such as RNF2, directly and functionally control powerful gene networks that are vital in multiple cancer processes.

Insights into the evolution of the nucleolus by an analysis of its protein domain repertoire.

Recently, the first investigation of nucleoli using mass spectrometry led to the identification of 271 proteins. This represents a rich resource for a comprehensive investigation of nucleolus evolution. We applied a protocol for the identification of known and novel conserved protein domains of the nucleolus, resulting in the identification of 115 known and 91 novel domain profiles. The phyletic distribution of nucleolar protein domains in a collection of complete proteomes of selected organisms from all domains of life confirms the archaebacterial origin of the core machinery for ribosome maturation and assembly, but also reveals substantial eubacterial and eukaryotic contributions to nucleolus evolution. We predict that, in different phases of nucleolus evolution, protein domains with different biochemical functions were recruited to the nucleolus. We suggest a model for the late and continuous evolution of the nucleolus in early eukaryotes and argue against an endosymbiotic origin of the nucleolus and the nucleus. Supplementary material for this article can be found on the BioEssays website at http://www.interscience.wiley.com/jpages/0265-9247/suppmat/index.html.