Biomedical subjects

Zhiping Weng

Publications and source records attributed to Zhiping Weng.

At least 19 recordsLinked to original sources

PubMed2026

Genome-wide survey of spliceosomal snRNA transcripts across hundreds of human biosamples reveals abundant transcription but low maturation level of snRNA variants.

Small nuclear RNAs (snRNAs) are essential components of the spliceosome and are encoded by large, multicopy gene families. However, their genome-wide identification and quantification have remained challenging due to high sequence similarity among family members. To address this, we utilized RAMPAGE (Rapid Amplification of cDNA Ends) data from the ENCODE project to comprehensively profile nascent transcription of spliceosomal snRNAs across 115 human biosamples. We identified 74 expressed snRNA variants, characterized by canonical promoter features including bidirectional transcription flanking a positioned nucleosome, active histone modifications, and evolutionary conservation- features largely absent from unexpressed variants. These transcriptional events were corroborated by total RNA-seq and Bru-seq data, yet the majority of these variants showed extremely low levels in small RNA-seq, indicating post-transcriptional bottlenecks for snRNA processing and maturation. Our findings reveal new layers of regulation in snRNA variant expression and suggest that selective post-transcriptional processing plays a critical role in shaping the functional snRNA repertoire and its contribution to splicing regulation.

Journal Article↗

PubMed2026

An encyclopedia of human enhancer-gene regulatory interactions.

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the effect of human genetic variation on disease1-6. Here we create and evaluate a resource of more than 92 million enhancer-gene regulatory interactions across 1,458 biosamples covering 369 cell types and tissues, by integrating predictive models, chromatin states, three-dimensional contacts and large-scale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,356 element-gene pairs measured in CRISPR perturbation experiments, more than 30,000 fine-mapped expression quantitative trait loci and 569 fine-mapped genome-wide association study (GWAS) variants linked to a probable causal gene. Using this framework, we develop ENCODE-rE2G, a predictive model achieving state-of-the-art performance across several prediction tasks, demonstrating that iterative perturbations and supervised machine learning can build increasingly accurate predictive models of enhancer regulation. Using ENCODE-rE2G, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, revealing global properties of enhancer networks, identifying differences in regulatory complexity across genes and improving analyses linking noncoding variants to target genes and cell types for common complex diseases. By interpreting the model, we find that beyond enhancer activity and three-dimensional enhancer-promoter contacts, additional features that guide enhancer-promoter communication include promoter class and enhancer-enhancer synergy. These genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

Humans↗

PubMed2022

Flnc: Machine Learning Improves the Identification of Novel Long Noncoding RNAs from Stand-Alone RNA-Seq Data.

Long noncoding RNAs (lncRNAs) play critical regulatory roles in human development and disease. Although there are over 100,000 samples with available RNA sequencing (RNA-seq) data, many lncRNAs have yet to be annotated. The conventional approach to identifying novel lncRNAs from RNA-seq data is to find transcripts without coding potential but this approach has a false discovery rate of 30-75%. Other existing methods either identify only multi-exon lncRNAs, missing single-exon lncRNAs, or require transcriptional initiation profiling data (such as H3K4me3 ChIP-seq data), which is unavailable for many samples with RNA-seq data. Because of these limitations, current methods cannot accurately identify novel lncRNAs from existing RNA-seq data. To address this problem, we have developed software, Flnc, to accurately identify both novel and annotated full-length lncRNAs, including single-exon lncRNAs, directly from RNA-seq data without requiring transcriptional initiation profiles. Flnc integrates machine learning models built by incorporating four types of features: transcript length, promoter signature, multiple exons, and genomic location. Flnc achieves state-of-the-art prediction power with an AUROC score over 0.92. Flnc significantly improves the prediction accuracy from less than 50% using the conventional approach to over 85%. Flnc is available via GitHub platform.

RNA-seq↗

PubMed2019

Genome-wide analysis of polymerase III-transcribed Alu elements suggests cell-type-specific enhancer function.

Alu elements are one of the most successful families of transposons in the human genome. A portion of Alu elements is transcribed by RNA Pol III, whereas the remaining ones are part of Pol II transcripts. Because Alu elements are highly repetitive, it has been difficult to identify the Pol III-transcribed elements and quantify their expression levels. In this study, we generated high-resolution, long-genomic-span RAMPAGE data in 155 biosamples all with matching RNA-seq data and built an atlas of 17,249 Pol III-transcribed Alu elements. We further performed an integrative analysis on the ChIP-seq data of 10 histone marks and hundreds of transcription factors, whole-genome bisulfite sequencing data, ChIA-PET data, and functional data in several biosamples, and our results revealed that although the human-specific Alu elements are transcriptionally repressed, the older, expressed Alu elements may be exapted by the human host to function as cell-type-specific enhancers for their nearby protein-coding genes.

Alu Elements↗

PubMed2006

Antigenicity and immunogenicity of HIV-1 consensus subtype B envelope glycoproteins.

"Centralized" (ancestral and consensus) HIV-1 envelope immunogens induce broadly cross-reactive T cell responses in laboratory animals; however, their potential to elicit cross-reactive neutralizing antibodies has not been fully explored. Here, we report the construction of a panel of consensus subtype B (ConB) envelopes and compare their biologic, antigenic, and immunogenic properties to those of two wild-type Env controls from individuals with early and acute HIV-1 infection. Glycoprotein expressed from full-length (gp160), uncleaved (gp160-UNC), truncated (gp145), and N-linked glycosylation site deleted (gp160-201N/S) versions of the ConB env gene were packaged into virions and, except for the fusion defective gp160-UNC, mediated infection via the CCR5 co-receptor. Pseudovirions containing ConB Envs were sensitive to neutralization by patient plasma and monoclonal antibodies, indicating the preservation of neutralizing epitopes found in contemporary subtype B viruses. When used as DNA vaccines in guinea pigs, ConB and wild-type env immunogens induced appreciable binding, but overall only low level neutralizing antibodies. However, all four ConB immunogens were significantly more potent than one wild-type vaccine at eliciting neutralizing antibodies against a panel of tier 1 and tier 2 viruses, and ConB gp145 and gp160 were significantly more potent than both wild-type vaccines at inducing neutralizing antibodies against tier 1 viruses. Thus, consensus subtype B env immunogens appear to be at least as good as, and in some instances better than, wild-type B env immunogens at inducing a neutralizing antibody response, and are amenable to further improvement by specific gene modifications.

AIDS Vaccines↗

PubMed2006

Global mapping of c-Myc binding sites and target gene networks in human B cells.

The protooncogene MYC encodes the c-Myc transcription factor that regulates cell growth, cell proliferation, cell cycle, and apoptosis. Although deregulation of MYC contributes to tumorigenesis, it is still unclear what direct Myc-induced transcriptomes promote cell transformation. Here we provide a snapshot of genome-wide, unbiased characterization of direct Myc binding targets in a model of human B lymphoid tumor using ChIP coupled with pair-end ditag sequencing analysis (ChIP-PET). Myc potentially occupies > 4,000 genomic loci with the majority near proximal promoter regions associated frequently with CpG islands. Using gene expression profiles with ChIP-PET, we identified 668 direct Myc-regulated gene targets, including 48 transcription factors, indicating that Myc is a central transcriptional hub in growth and proliferation control. This first global genomic view of Myc binding sites yields insights of transcriptional circuitries and cis regulatory modules involving Myc and provides a substantial framework for our understanding of mechanisms of Myc-induced tumorigenesis.

B-Lymphocytes↗

PubMed2006

Ancestral and consensus envelope immunogens for HIV-1 subtype C.

Immunogens based on "centralized" (ancestral or consensus) HIV-1 sequences minimize the genetic distance between vaccine strains and contemporary viruses and should thus elicit immune responses that recognize a broader spectrum of viral variants. However, the biologic, antigenic and immunogenic properties of such inferred gene products have to be validated experimentally. Here, we report the construction and characterization of the first full-length ancestral (AncC) and consensus (ConC) env genes of HIV-1 (group M) subtype C. The codon-usage-optimized genes expressed high levels of envelope glycoproteins that were incorporated into HIV-1 virions, mediated infection via the CCR5 co-receptor and retained neutralizing epitopes as recognized by plasma from patients with chronic HIV-1 subtype C infection. Guinea pigs immunized with AncC and ConC env DNA developed high titer binding, but no appreciable homologous or heterologous neutralizing antibodies. When tested by immunoblot analysis, sera from AncC and ConC env immunized guinea pigs recognized a greater number of primary subtype C envelope glycoproteins than sera from guinea pigs immunized with a contemporary subtype C env control. Mice immunized with AncC and ConC env DNA developed gamma interferon T cell responses that recognized overlapping peptides from the cognate ConC and a heterologous subtype C Env control. Thus, both AncC and ConC env genes expressed functional envelope glycoproteins that were immunogenic in laboratory animals and elicited humoral and cellular immune responses of comparable breadth and magnitude. These results establish the utility of centralized HIV-1 subtype C Env immunogens and warrant their continued evaluation as potential components of future AIDS vaccines.

AIDS Vaccines↗

PubMed2006

A global map of p53 transcription-factor binding sites in the human genome.

The ability to derive a whole-genome map of transcription-factor binding sites (TFBS) is crucial for elucidating gene regulatory networks. Herein, we describe a robust approach that couples chromatin immunoprecipitation (ChIP) with the paired-end ditag (PET) sequencing strategy for unbiased and precise global localization of TFBS. We have applied this strategy to map p53 targets in the human genome. From a saturated sampling of over half a million PET sequences, we characterized 65,572 unique p53 ChIP DNA fragments and established overlapping PET clusters as a readout to define p53 binding loci with remarkable specificity. Based on this information, we refined the consensus p53 binding motif, identified at least 542 binding loci with high confidence, discovered 98 previously unidentified p53 target genes that were implicated in novel aspects of p53 functions, and showed their clinical relevance to p53-dependent tumorigenesis in primary cancer samples.

Binding Sites↗

PubMed2005

Main-chain conformational tendencies of amino acids.

A Ramachandran plot is a visual representation of the main-chain conformational tendencies of an amino acid. Despite forty years of research, the shape of Ramachandran plots is still a matter of debate. The issue in making a Ramachandran plot based on experimental data is deciding whether sparse data represent genuine conformations. We present here a simple solution to settle the ambiguities of the sparse data, and explain how we verified the accuracies of our plots using an independent dataset. To obtain our results, we then measured the pair-wise distances of main-chain conformational tendencies among amino acids, and showed that the conformational relationships of amino acids are well preserved in a two-dimensional map, leading to the conclusion that the conformational diversity space of amino acids is largely two dimensional. We further noticed that amino acids in early and late evolutionary stages are located in different zones in the two-dimensional map. In addition to these conclusions, we here present an amino acid substitution table derived from experimental data.

Amino Acids↗

PubMed2005

Less is more: towards an optimal universal description of protein folds.

MOTIVATION: Identification and characterization of protein structure regularities can reveal the mechanisms governing protein structure, function and evolution. Here we focus on an intermediate level of regularity. We have developed automated methods to systematically construct a dictionary of supersecondary structures that can be used as 'protein parts' to describe fold-sized structures. RESULTS: The dictionary was constructed by aligning representative structures of all known folds, clustering similar substructures and selecting the most descriptive substructures in a minimum description length fashion. We show that the dictionary is compact and descriptive, capable of describing a substantial fraction of all known protein folds. We performed simulations using independent sets of training and testing folds. Dictionaries generated using the training set had high coverage over the folds in the testing set, suggesting that dictionary entries reflect general features of protein structures and should be capable of describing novel protein folds.

Algorithms↗

PubMed2005

Genome-wide decoding of hierarchical modular structure of transcriptional regulation by cis-element and expression clustering.

MOTIVATION: A holistic approach to the study of cellular processes is identifying both gene-expression changes and regulatory elements promoting such changes. Cellular regulatory processes can be viewed as transcriptional modules (TMs), groups of coexpressed genes regulated by groups of transcription factors (TFs). We set out to devise a method that would identify TMs while avoiding arbitrary thresholds on TM sizes and number. METHOD: Assuming that gene expression is determined by TFs that bind to the gene's promoter, clustering of genes based on TF binding sites (cis-elements) should create gene groups similar to those obtained by gene expression clustering. Intersections between the expression and cis-element-based gene clusters reveal TMs. Statistical significance assigned to each TM allows identification of regulatory units of any size. RESULTS: Our method correctly identifies the number and sizes of TMs on simulated datasets. We demonstrate that yeast experimental TMs are biologically relevant by comparing them with MIPS and GO categories. Our modules are in statistically significant agreement with TMs from other research groups. This work suggests that there is no preferential division of biological processes into regulatory units; each degree of partitioning exhibits a slice of biological network revealing hierarchical modular organization of transcriptional regulation.

Algorithms↗

PubMed2005

ZDOCK and RDOCK performance in CAPRI rounds 3, 4, and 5.

We present an evaluation of the results of our ZDOCK and RDOCK algorithms in Rounds 3, 4, and 5 of the protein docking challenge CAPRI. ZDOCK is a Fast Fourier Transform (FFT)-based, initial-stage rigid-body docking algorithm, and RDOCK is an energy minimization algorithm for refining and reranking ZDOCK results. Of the 9 targets for which we submitted predictions, we attained at least acceptable accuracy for 7, at least medium accuracy for 6, and high accuracy for 3. These results are evidence that ZDOCK in combination with RDOCK is capable of making accurate predictions on a diverse set of protein complexes.

Algorithms↗

PubMed2005

Protein-Protein Docking Benchmark 2.0: an update.

We present a new version of the Protein-Protein Docking Benchmark, reconstructed from the bottom up to include more complexes, particularly focusing on more unbound-unbound test cases. SCOP (Structural Classification of Proteins) was used to assess redundancy between the complexes in this version. The new benchmark consists of 72 unbound-unbound cases, with 52 rigid-body cases, 13 medium-difficulty cases, and 7 high-difficulty cases with substantial conformational change. In addition, we retained 12 antibody-antigen test cases with the antibody structure in the bound form. The new benchmark provides a platform for evaluating the progress of docking methods on a wide variety of targets. The new version of the benchmark is available to the public at http://zlab.bu.edu/benchmark2.

Algorithms↗

PubMed2005

Genetic and pharmacological inactivation of adenosine A2A receptor reveals an Egr-2-mediated transcriptional regulatory network in the mouse striatum.

The adenosine A2A receptor (A2AR) is highly expressed in the striatum, where it modulates motor and emotional behaviors. We used both microarray and bioinformatics analyses to compare gene expression profiles by genetic and pharmacological inactivation of A2AR and inferred an A2AR-controlled transcription network in the mouse striatum. A comparison between vehicle (VEH)-treated A2AR knockout (KO) mice (A2AR KO-VEH) and wild-type (WT) mice (WT-VEH) revealed 36 upregulated genes that were partially mimicked by treatment with SCH-58261 (SCH; an A2AR antagonist) and 54 downregulated genes that were not mimicked by SCH treatment. We validated the A2AR as a specific drug target for SCH by comparing A2AR KO-SCH and A2AR KO-VEH groups. The unique downregulation effect of A2AR KO was confirmed by comparing A2AR KO-SCH with WT-SCH gene groups. The distinct striatal gene expression profiles induced by A2AR KO and SCH should provide clues to the molecular mechanisms underlying the different phenotypes observed after genetic and pharmacological inactivation of A2AR. Furthermore, bioinformatics analysis discovered that Egr-2 binding sites were statistically overrepresented in the proximal promoters of A2AR KO-affected genes relative to the unaffected genes. This finding was further substantiated by the demonstration that the Egr-2 mRNA level increased in the striatum of both A2AR KO and SCH-treated mice and that striatal Egr-2 binding activity in the promoters of two A2AR KO-affected genes was enhanced in A2AR KO mice as assayed by chromatin immunoprecipitation. Taken together, these results strongly support the existence of an Egr-2-directed transcriptional regulatory network controlled by striatal A2ARs.

Animals↗

PubMed2005

Structure, function, and evolution of transient and obligate protein-protein interactions.

Recent analyses of high-throughput protein interaction data coupled with large-scale investigations of evolutionary properties of interaction networks have left some unanswered questions. To what extent do protein interactions act as constraints during evolution of the protein sequence? How does the type of interaction, specifically transient or obligate, play into these constraints? Are the mutations in the binding site of an interacting protein correlated with mutations in the binding site of its partner? We address these and other questions by relying on a carefully curated dataset of protein complex structures. Results point to the importance of distinguishing between transient and obligate interactions. We conclude that residues in the interfaces of obligate complexes tend to evolve at a relatively slower rate, allowing them to coevolve with their interacting partners. In contrast, the plasticity inherent in transient interactions leads to an increased rate of substitution for the interface residues and leaves little or no evidence of correlated mutations across the interface.

Amino Acid Substitution↗

PubMed2005

FAST: a novel protein structure alignment algorithm.

We present a novel algorithm named FAST for aligning protein three-dimensional structures. FAST uses a directionality-based scoring scheme to compare the intra-molecular residue-residue relationships in two structures. It employs an elimination heuristic to promote sparseness in the residue-pair graph and facilitate the detection of the global optimum. In order to test the overall accuracy of FAST, we determined its sensitivity and specificity with the SCOP classification (version 1.61) as the gold standard. FAST achieved higher sensitivities than several existing methods (DaliLite, CE, and K2) at all specificity levels. We also tested FAST against 1033 manually curated alignments in the HOMSTRAD database. The overall agreement was 96%. Close inspection of examples from broad structural classes indicated the high quality of FAST alignments. Moreover, FAST is an order of magnitude faster than other algorithms that attempt to establish residue-residue correspondence. Typical pairwise alignments take FAST less than a second with a Pentium III 1.2GHz CPU. FAST software and a web server are available at http://biowulf.bu.edu/FAST/.

Algorithms↗

PubMed2005

Assessing computational tools for the discovery of transcription factor binding sites.

The prediction of regulatory elements is a problem where computational methods offer great hope. Over the past few years, numerous tools have become available for this task. The purpose of the current assessment is twofold: to provide some guidance to users regarding the accuracy of currently available tools in various settings, and to provide a benchmark of data sets for assessing future tools.

Amino Acid Motifs↗

PubMed2005

An avidin-like domain that does not bind biotin is adopted for oligomerization by the extracellular mosaic protein fibropellin.

The protein avidin found in egg white seems optimized for binding the small vitamin biotin as a stable homotetramer. Indeed, along with its streptavidin ortholog in the bacterium Streptomyces avidinii, this protein shows the strongest known noncovalent bond of a protein with a small ligand. A third known member of the avidin family, as similar to avidin as is streptavidin, is found at the C-terminal ends of the multidomain fibropellin proteins found in sea urchin. The fibropellins form a layer known as the apical lamina that surrounds the sea urchin embryo throughout development. Based upon the structure of avidin, we deduced a structural model for the avidin-like domain of the fibropellins and found that computational modeling predicts a lack of biotin binding and the preservation of tetramerization. To test this prediction we expressed and purified the fibropellin avidin-like domain and found it indeed to be a homotetramer incapable of binding biotin. Several lines of evidence suggest that the avidin-like domain causes the entire fibropellin protein to tetramerize. We suggest that the presence of the avidin-like domain serves a structural (tetrameric form) rather than functional (biotin-binding) role and may therefore be a molecular instance of exaptation-the modification of an existing function toward a new function. Finally, based upon the oligomerization of the avidin-like domain, we propose a model for the overall structure of the apical lamina.

Amino Acid Sequence↗