James Zou

Analysis of protein-coding genetic variation in 60,706 humans

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human ‘knockout’ variants in protein-coding genes.

Locus-specific editing of histone modifications at endogenous enhancers using programmable TALE-LSD1 fusions

Mammalian gene regulation is dependent on tissue-specific enhancers that can act across large distances to influence transcriptional activity. Mapping experiments have identified hundreds of thousands of putative enhancers whose functionality is supported by cell type–specific chromatin signatures and striking enrichments for disease-associated sequence variants. However, these studies did not address the in vivo functions of the putative elements or their chromatin states and did not determine which genes, if any, a given enhancer regulates. Here we present a strategy to investigate endogenous regulatory elements by selectively altering their chromatin state using programmable reagents. Transcription activator–like (TAL) effector repeat domains fused to the LSD1 histone demethylase efficiently remove enhancer-associated chromatin modifications from target loci, without affecting control regions. We find that inactivation of enhancer chromatin by these fusion proteins frequently causes downregulation of proximal genes, revealing enhancer target genes. Our study demonstrates the potential of epigenome editing tools to characterize an important class of functional genomic elements.

Genome-wide analysis reveals conserved and divergent features of Notch1/RBPJ binding in human and murine T-lymphoblastic leukemia cells

Notch1 regulates gene expression by associating with the DNA-binding factor RBPJ and is oncogenic in murine and human T-cell progenitors. Using ChIP-Seq, we find that in human and murine T-lymphoblastic leukemia (TLL) genomes Notch1 binds preferentially to promoters, to RBPJ binding sites, and near imputed ZNF143, ETS, and RUNX sites. ChIP-Seq confirmed that ZNF143 binds to ∼40% of Notch1 sites. Notch1/ZNF143 sites are characterized by high Notch1 and ZNF143 signals, frequent cobinding of RBPJ (generally through sites embedded within ZNF143 motifs), strong promoter bias, and relatively low mean levels of activating chromatin marks. RBPJ and ZNF143 binding to DNA is mutually exclusive in vitro, suggesting RBPJ/Notch1 and ZNF143 complexes exchange on these sites in cells. K-means clustering of Notch1 binding sites and associated motifs identified conserved Notch1-RUNX, Notch1-ETS, Notch1-RBPJ, Notch1-ZNF143, and Notch1-ZNF143-ETS clusters with different genomic distributions and levels of chromatin marks. Although Notch1 binds mainly to gene promoters, ∼75% of direct target genes lack promoter binding and are presumably regulated by enhancers, which were identified near MYC, DTX1, IGF1R, IL7R, and the GIMAP cluster. Human and murine TLL genomes also have many sites that bind only RBPJ. Murine RBPJ-only sites are highly enriched for imputed REST (a DNA-binding transcriptional repressor) sites, whereas human RPBJ-only sites lack REST motifs and are more highly enriched for imputed CREB sites. Thus, there is a conserved network of cis-regulatory factors that interacts with Notch1 to regulate gene expression in TLL cells, as well as unique classes of divergent RBPJ-only sites that also likely regulate transcription.

Epigenome-wide association studies without the need for cell-type composition

In epigenome-wide association studies, cell-type composition often differs between cases and controls, yielding associations that simply tag cell type rather than reveal fundamental biology. Current solutions require actual or estimated cell-type composition—information not easily obtainable for many samples of interest. We propose a method, FaST-LMM-EWASher, that automatically corrects for cell-type composition without the need for explicit knowledge of it, and then validate our method by comparison with the state-of-the-art approach. Corresponding software is available from http://www.microsoft.com/science/.

Epstein-Barr virus exploits intrinsic B-lymphocyte transcription programs to achieve immortal cell growth

Epstein-Barr virus nuclear antigen 2 (EBNA2) regulation of transcription through the cell transcription factor RBPJ is essential for resting B-lymphocyte (RBL) conversion to immortal lymphoblast cell lines (LCLs). ChIP-seq of EBNA2 and RBPJ sites in LCL DNA found EBNA2 at 5,151 and RBPJ at 10,529 sites. EBNA2 sites were enriched for RBPJ (78%), early B-cell factor (EBF, 39%), RUNX (43%), ETS (39%), NFκB (22%), and PU.1 (22%) motifs. These motif associations were confirmed by LCL RBPJ ChIP-seq finding 72% RBPJ occupancy and Encyclopedia Of DNA Elements LCL ChIP-seq finding EBF, NFκB RELA, and PU.1 at 54%, 31%, and 17% of EBNA2 sites. EBNA2 and RBPJ were predominantly at intergene and intron sites and only 14% at promoter sites. K-means clustering of EBNA2 site transcription factors identified RELA-ETS, EBF-RUNX, EBF, ETS, RBPJ, and repressive RUNX clusters, which ranked from highest to lowest in H3K4me1 signals and nucleosome depletion, indicative of active chromatin. Surprisingly, although quantitatively less, the same genome sites in RBLs exhibited similar high-level H3K4me1 signals and nucleosome depletion. The EBV genome also had an LMP1 promoter EBF site, which proved critical for EBNA2 activation. LCL HiC data mapped intergenic EBNA2 sites to EBNA2 up-regulated genes. FISH and chromatin conformation capture linked EBNA2/RBPJ enhancers 428 kb 5′ of MYC to MYC. These data indicate that EBNA2 evolved to target RBL H3K4me1 modified, nucleosome-depleted, nonpromoter sites to drive B-lymphocyte proliferation in primary human infection. The primed RBL program likely supports antigen-induced proliferation.

Epstein-Barr virus nuclear antigens 3C and 3A maintain lymphoblastoid cell growth by repressing p16INK4A and p14ARF expression

Epstein-Barr virus (EBV) nuclear antigen 3C (EBNA3C) and EBNA3A are each essential for EBV conversion of primary human B lymphocytes into continuously proliferating lymphoblast cell lines (LCLs) and for maintaining LCL growth. We now find that EBNA3C and EBNA3As essential roles are to repress p16INK4A and p14ARF. In the absence of EBNA3C or EBNA3A, p16INK4A and p14ARF expression increased and cell growth ceased. EBNA3C inactivation did not alter p16INK4A promoter CpG methylation, but reduced already low H3K27me3, relative to resting B cells, and increased H3K4me3 and H3-acetylation, linking EBNA3C inactivation to histone modifications associated with increased transcription. Importantly, knockdown of p16INK4A or p14ARF partially rescued LCLs from EBNA3C or EBNA3A inactivation-induced growth arrest and knockdown of both rescued LCL growth, confirming central roles for p16INK4A and p14ARF in LCL growth arrest following EBNA3C or EBNA3A inactivation. Moreover, blockade of p16INK4A and p14ARF effects on pRb and p53 by human papilloma virus type 16 E7 and E6 expression, sustained LCL growth after EBNA3C or EBNA3A inactivation. These data indicate that EBNA3C and EBNA3A joint repression of CDKN2A p16INK4A and p14ARF is essential for LCL growth.

Sparse PCA corrects for cell type heterogeneity in epigenome-wide association studies

In epigenome-wide association studies (EWAS), different methylation profiles of distinct cell types may lead to false discoveries. We introduce ReFACTor, a method based on principal component analysis (PCA) and designed for the correction of cell type heterogeneity in EWAS. ReFACTor does not require knowledge of cell counts, and it provides improved estimates of cell type composition, resulting in improved power and control for false positives in EWAS. Corresponding software is available at http://www.cs.tau.ac.il/~heran/cozygene/software/refactor.html.

Quantifying unobserved protein-coding variants in human populations provides a roadmap for large-scale sequencing projects

As new proposals aim to sequence ever larger collection of humans, it is critical to have a quantitative framework to evaluate the statistical power of these projects. We developed a new algorithm, UnseenEst, and applied it to the exomes of 60,706 individuals to estimate the frequency distribution of all protein-coding variants, including rare variants that have not been observed yet in the current cohorts. Our results quantified the number of new variants that we expect to identify as sequencing cohorts reach hundreds of thousands of individuals. With 500K individuals, we find that we expect to capture 7.5% of all possible loss-of-function variants and 12% of all possible missense variants. We also estimate that 2,900 genes have loss-of-function frequency of <0.00001 in healthy humans, consistent with very strong intolerance to gene inactivation.

A slime mold solver for linear programming problems

Physarum polycephalum (true slime mold) has recently emerged as a fascinating example of biological computation through morphogenesis. Despite being a single cell organism, experiments have observed that through its growth process, the Physarum is able to solve various minimum cost flow problems. This paper analyzes a mathematical model of the Physarum growth dynamics. We show how to encode general linear programming (LP) problems as instances of the Physarum. We prove that under the growth dynamics, the Physarum is guaranteed to converge to the optimal solution of the LP. We further derive an efficient discrete algorithm based on the Physarum model, and experimentally verify its performance on assignment problems.

Strategic Voting Behavior in Doodle Polls

Finding a common time slot for a group event is a daily conundrum and illustrates key features of group decision-making. It is a complex interplay of individual incentives and group dynamics. A participant would like the final time to be convenient for her, but she is also expected to be cooperative towards other peoples preferences. We combine large-scale data analysis with theoretical models from the voting literature to investigate strategic behaviors in event scheduling. We analyze all Doodle polls created in the US from July-September 2011 (over 340,000 polls), consisting of both hidden polls (a user cannot see other responses) and open polls (a user can see all previous responses). By analyzing the differences in behavior in hidden and open polls, we gain unique insights into strategies that people apply in a natural decision-making setting. Responders in open polls are more likely to approve slots that are very popular or very unpopular, but not intermediate slots. We show that this behavior is inconsistent with models that have been proposed in the voting literature, and propose a new model based on combining personal and social utilities to explain the data.