ENCODE 3 (2012-2017) expanded production and added new types of assays 8 (Fig. 1, Extended Data Fig. 1), which revealed landscapes of RNA binding and the 3D organization of chromatin via methods such as chromatin interaction analysis by paired-end tagging (ChIA-PET) and Hi-C chromosome conformation capture. Phases 2 and 3 delivered 9,239 experiments (7,495 in human and 1,744 in mouse) in more than 500 cell types and tissues, including mapping of transcribed regions and transcript isoforms, regions of transcripts recognized by RNA-binding proteins, transcription factor binding regions, and regions that harbour specific histone modifications, open chromatin, and 3D chromatin interactions. The results of all of these experiments are available at the ENCODE portal (http://www.encodeproject.org). These efforts, combined with those of related projects and many other laboratories, have produced a greatly enhanced view of the human genome (Fig. 2), identifying 20,225 protein-coding and 37,595 noncoding genes

In many human diseases, associated genetic changes tend to occur within non-coding regions, whose effect might be related to transcriptional control. A central goal in human genetics is to understand the function of such non-coding regions: Given a region that is statistically associated with changes in gene expression (expression Quantitative Trait Locus; eQTL), does it in fact play a regulatory role? And if so, how is this role “coded” in its sequence? These questions were the subject of the Critical Assessment of Genome Interpretation eQTL challenge. Participants were given a set of sequences that flank eQTLs in humans and were asked to predict whether these are capable of regulating transcription (as evaluated by massively parallel reporter assays), and whether this capability changes between alternative alleles. Here, we report lessons learned from this community effort. By inspecting predictive properties in isolation, and conducting meta-analysis over the competing methods, we find that using chromatin accessibility and transcription factor binding as features in an ensemble of classifiers or regression models leads to the most accurate results. We then characterize the loci that are harder to predict, putting the spotlight on areas of weakness, which we expect to be the subject of future studies.

Latent infection of B lymphocytes by Epstein-Barr virus (EBV) in vitro results in their immortalization into lymphoblastoid cell lines (LCLs); this latency program is controlled by the EBNA2 viral transcriptional activator, which targets promoters via RBPJ, a DNA binding protein in the Notch signaling pathway. Three other EBNA3 proteins (EBNA3A, EBNA3B, and EBNA3C) interact with RBPJ to regulate cell gene expression. The mechanism by which EBNAs regulate different genes via RBPJ remains unclear. Our chromatin immunoprecipitation with deep sequencing (ChIP-seq) analysis of the EBNA3 proteins analyzed in concert with prior EBNA2 and RBPJ data demonstrated that EBNA3A, EBNA3B, and EBNA3C bind to distinct, partially overlapping genomic locations. Although RBPJ interaction is critical for EBNA3A and EBNA3C growth effects, only 30 to 40% of EBNA3-bound sites colocalize with RBPJ. Using LCLs conditional for EBNA3A or EBNA3C activity, we demonstrate that EBNA2 binding at sites near EBNA3A-or EBNA3C-regulated genes is specifically regulated by the respective EBNA3. To investigate EBNA3 binding specificity, we identified sequences and transcription factors enriched at EBNA3A-, EBNA3B-, and EBNA3C-bound sites. This confirmed the prior observation that IRF4 is enriched at EBNA3A-and EBNA3C-bound sites and revealed IRF4 enrichment at EBNA3B-bound sites. Using IRF4-negative BJAB cells, we demonstrate that IRF4 is essential for EBNA3C, but not EBNA3A or EBNA3B, binding to specific sites. These results support a model in which EBNA2 and EBNA3s compete for distinct subsets of RBPJ sites to regulate cell genes and where EBNA3 subset specificity is determined by interactions with other cell transcription factors. IMPORTANCE Epstein-Barr virus (EBV) latent gene products cause human cancers and transform B lymphocytes into immortalized lymphoblastoid cell lines in vitro.EBV nuclear antigens (EBNAs) and membrane proteins constitutively activate pathways important for lymphocyte growth and survival. An important unresolved question is how four different EBNAs (EBNA2, -3A, -3B, and -3C) exert unique effects via a single transcription factor, RBPJ. Here, we report that each EBNA binds to distinct but partially overlapping sets of genomic sites. EBNA3A and EBNA3C specifically regulate EBNA2's access to different RBPJ sites, providing a mechanism by which each EBNA can regulate distinct cell genes. We show that IRF4, an essential regulator of B cell differentiation, is critical for EBNA3C binding specificity; EBNA3A and EBNA3B specificities are likely due to interactions with other cell transcription factors. EBNA3 titration of EBNA2 transcriptional function at distinct sites likely limits cell defenses that would be triggered by unchecked EBNA2 prooncogenic activity. E pstein-Barr virus (EBV) is a herpesvirus that infects over 90% of the population by adulthood. Primary EBV infection usually presents as a nonspecific illness in early childhood but often manifests as infectious mononucleosis in adolescents (1). Thereafter, EBV es...

Epstein-Barr virus (EBV) is a human herpesvirus that is associated with lymphomas as well as nasopharyngeal and gastric carcinomas. Although carcinomas account for almost 90% of EBV-associated cancers, progress in examining EBV’s role in their pathogenesis has been limited by difficulty in establishing latent infection in nontransformed epithelial cells. Recently, EBV infection of human telomerase reverse transcriptase (hTERT)-immortalized normal oral keratinocytes (NOKs) has emerged as a model that recapitulates aspects of EBV infection in vivo, such as differentiation-associated viral replication. Using uninfected NOKs and NOKs infected with the Akata strain of EBV (NOKs-Akata), we examined changes in gene expression due to EBV infection and differentiation. Latent EBV infection produced very few significant gene expression changes in undifferentiated NOKs but significantly reduced the extent of differentiation-induced gene expression changes. Gene set enrichment analysis revealed that differentiation-induced downregulation of the cell cycle and metabolism pathways was markedly attenuated in NOKs-Akata relative to that in uninfected NOKs. We also observed that pathways induced by differentiation were less upregulated in NOKs-Akata. We observed decreased differentiation markers and increased suprabasal MCM7 expression in NOKs-Akata versus NOKs when both were grown in raft cultures, consistent with our transcriptome sequencing (RNA-seq) results. These effects were also observed in NOKs infected with a replication-defective EBV mutant (AkataΔRZ), implicating mechanisms other than lytic-gene-induced host shutoff. Our results help to define the mechanisms by which EBV infection alters keratinocyte differentiation and provide a basis for understanding the role of EBV in epithelial cancers. IMPORTANCE Latent infection by Epstein-Barr virus (EBV) is an early event in the development of EBV-associated carcinomas. In oral epithelial tissues, EBV establishes a lytic infection of differentiated epithelial cells to facilitate the spread of the virus to new hosts. Because of limitations in existing model systems, the effects of latent EBV infection on undifferentiated and differentiating epithelial cells are poorly understood. Here, we characterize latent infection of an hTERT-immortalized oral epithelial cell line (NOKs). We find that although EBV expresses a latency pattern similar to that seen in EBV-associated carcinomas, infection of undifferentiated NOKs results in differential expression of a small number of host genes. In differentiating NOKs, however, EBV has a more substantial effect, reducing the extent of differentiation and delaying the exit from the cell cycle. This effect may synergize with preexisting cellular abnormalities to prevent exit from the cell cycle, representing a critical step in the development of cancer.

Segmental duplications and other highly repetitive regions of genomes contribute significantly to cells’ regulatory programs. Advancements in next generation sequencing enabled genome-wide profiling of protein-DNA interactions by chromatin immunoprecipitation followed by high throughput sequencing (ChIP-seq). However, interactions in highly repetitive regions of genomes have proven difficult to map since short reads of 50–100 base pairs (bps) from these regions map to multiple locations in reference genomes. Standard analytical methods discard such multi-mapping reads and the few that can accommodate them are prone to large false positive and negative rates. We developed Perm-seq, a prior-enhanced read allocation method for ChIP-seq experiments, that can allocate multi-mapping reads in highly repetitive regions of the genomes with high accuracy. We comprehensively evaluated Perm-seq, and found that our prior-enhanced approach significantly improves multi-read allocation accuracy over approaches that do not utilize additional data types. The statistical formalism underlying our approach facilitates supervising of multi-read allocation with a variety of data sources including histone ChIP-seq. We applied Perm-seq to 64 ENCODE ChIP-seq datasets from GM12878 and K562 cells and identified many novel protein-DNA interactions in segmental duplication regions. Our analysis reveals that although the protein-DNA interactions sites are evolutionarily less conserved in repetitive regions, they share the overall sequence characteristics of the protein-DNA interactions in non-repetitive regions.