Coral: Clear and Customizable Visualization of Human Kinome Data

Metz, K.S., Deoudes, E.M., Berginsky, M.E., Jimenez-Ruiz, I., Aksoy, B.A., Hammerbacher, J., Gomez, S.M., Phanstiel, D.H. Cell Systems (2018)

Protein kinases represent one of the largest gene families in eukaryotes and play roles in a wide range of cell signaling processes and human diseases. Current tools for visualizing kinase data in the context of the human kinome superfamily are limited to encoding data through the addition of nodes to a low-resolution image of the kinome tree. We present Coral, a user-friendly interactive web application for visualizing both quantitative and qualitative data. Unlike previous tools, Coral can encode data in three features (node color, node size, and branch color), allows three modes of kinome visualization (the traditional kinome tree as well as radial and dynamic force networks), and generates high-resolution scalable vector graphics files suitable for publication without the need for refinement using graphics editing software. Due to its user-friendly, interactive, and highly customizable design, Coral is broadly applicable to high-throughput studies of the human kinome. The source code and web application are available at github.com/dphansti/CORAL and phanstiel-lab.med.unc.edu/Coral, respectively.

Static and Dynamic DNA Loops form AP-1-Bound Activation Hubs during Macrophage Development

Phanstiel, D.H.*, Van Bortle, K.*, Spacek D.V., Hess G.T., Saad Shamim M., Machol I., Love M.I., Lieberman Aiden E., Bassik M.C., Snyder, M.P.   Molecular Cell (2017)

The three-dimensional arrangement of the human genome comprises a complex network of structural and regulatory chromatin loops important for coordinating changes in transcription during human development. To better understand the mechanisms underlying context-specific 3D chromatin structure and transcription during cellular differentiation, we generated comprehensive in situ Hi-C maps of DNA loops in human monocytes and differentiated macrophages. We demonstrate that dynamic looping events are regulatory rather than structural in nature and uncover widespread coordination of dynamic enhancer activity at preformed and acquired DNA loops. Enhancer-bound loop formation and enhancer-activation of preformed loops together form multi-loop activation hubs at key macrophage genes. Activation hubs connect 3.4 enhancers per promoter and exhibit a strong enrichment for Activator Protein 1 (AP-1) binding events, suggesting multi-loop activation hubs involving cell-type specific transcription factors may represent an important class of regulatory chromatin structures for the spatiotemporal control of transcription.

Mango: a bias-correcting ChIA-PET analysis pipeline

Phanstiel, D.H., Boyle,A.P., Heidari, N., Snyder, M.P.   Bioinformatics (2015)

Chromatin Interaction Analysis by Paired-End Tag sequencing (ChIA-PET) is an established method for detecting genome-wide looping interactions at high resolution. Current ChIA-PET analysis software packages either fail to correct for non-specific interactions due to genomic proximity or only address a fraction of the steps required for data processing. We present Mango, a complete ChIA-PET data analysis pipeline that provides statistical confidence estimates for interactions and corrects for major sources of bias including differential peak enrichment and genomic proximity.

Comparison to the existing software packages, ChIA-PET Tool and ChiaSig, revealed that Mango interactions exhibit much better agreement with high-resolution Hi-C data. Importantly, Mango executes all steps required for processing ChIA-PET datasets, whereas ChiaSig only completes 20% of the required steps. Application of Mango to multiple available ChIA-PET datasets permitted the independent rediscovery of known trends in chromatin loops including enrichment of CTCF, RAD21, SMC3 and ZNF143 at the anchor regions of interactions and strong bias for convergent CTCF motifs.

Mango is open source and distributed through github at https://github.com/dphansti/mango.

Sushi.R: flexible, quantitative and integrative genomic visualizations for publication-quality multi-panel figures

Phanstiel, D.H., Boyle A.P., Araya C.L., Snyder M.P.   Bioinformatics (2014)

Interpretation and communication of genomic data require flexible and quantitative tools to analyze and visualize diverse data types, and yet, a comprehensive tool to display all common genomic data types in publication quality figures does not exist to date. To address this shortcoming, we present Sushi.R, an R/Bioconductor package that allows flexible integration of genomic visualizations into highly customizable, publication-ready, multi-panel figures from common genomic data formats including Browser Extensible Data (BED), bedGraph, and Browser Extensible Data Paired-End (BEDPE). Sushi.R is open source and made publicly available through GitHub (https://github.com/dphansti/Sushi) and Bioconductor (http://bioconductor.org/packages/release/bioc/html/Sushi.html).

Genome-wide map of regulatory interactions in the human genome

Heidari N.*, Phanstiel, D.H.*, He C., Grubert F., Jahanbani F., Kasowski M., Zhang M.Q., Snyder M.P.   Genome Research (2014)

Increasing evidence suggests that interactions between regulatory genomic elements play an important role in regulating gene expression. We generated a genome-wide interaction map of regulatory elements in human cells (ENCODE tier 1 cells, K562, GM12878) using Chromatin Interaction Analysis by Paired-End Tag sequencing (ChIA-PET) experiments targeting six broadly distributed factors. Bound regions covered 80% of DNase I hypersensitive sites including 99.7% of TSS and 98% of enhancers. Correlating this map with ChIP-seq and RNA-seq data sets revealed cohesin, CTCF, and ZNF143 as key components of three-dimensional chromatin structure and revealed how the distal chromatin state affects gene transcription. Comparison of interactions between cell types revealed that enhancer-promoter interactions were highly cell-type-specific. Construction and comparison of distal and proximal regulatory networks revealed stark differences in structure and biological function. Proximal binding events are enriched at genes with housekeeping functions, while distal binding events interact with genes involved in dynamic biological processes including response to stimulus. This study reveals new mechanistic and functional insights into regulatory region organization in the nucleus.

Proteomic and phosphoproteomic comparison of human ES and iPS cells

Phanstiel, D.H.*, Brumbaugh J.*, Wenger C.D., Tian S., Probasco M.D., Bailey D.J., Swaney D.L., Tervo M.A., Bolin J.M., Ruotti V., Stewart R., Thomson J.A., Coon J.J.   Nature Methods (2011)

Combining high-mass-accuracy mass spectrometry, isobaric tagging and software for multiplexed, large-scale protein quantification, we report deep proteomic coverage of four human embryonic stem cell and four induced pluripotent stem cell lines in biological triplicate. This 24-sample comparison resulted in a very large set of identified proteins and phosphorylation sites in pluripotent cells. The statistical analysis afforded by our approach revealed subtle but reproducible differences in protein expression and protein phosphorylation between embryonic stem cells and induced pluripotent cells. Merging these results with RNA-seq analysis data, we found functionally related differences across each tier of regulation. We also introduce the Stem Cell-Omics Repository (SCOR), a resource to collate and display quantitative information across multiple planes of measurement, including mRNA, protein and post-translational modifications.

Mass spectrometry identifies and quantifies 74 unique histone H4 isoforms in differentiating human embryonic stem cells

Phanstiel, D.H., Brumbaugh, J., Berggren, W.T., Conard, K., Feng, X., Levenstein, M.E., McAlister, G.C., Thomson, J.A., Coon, J.J.   Proceedings of the National Academy of Sciences (2008)

Epigenetic regulation through chromatin is thought to play a critical role in the establishment and maintenance of pluripotency. Traditionally, antibody-based technologies were used to probe for specific posttranslational modifications (PTMs) present on histone tails, but these methods do not generally reveal the presence of multiple modifications on a single-histone tail (combinatorial codes). Here, we describe technology for the discovery and quantification of histone combinatorial codes that is based on chromatography and mass spectrometry. We applied this methodology to decipher 74 discrete combinatorial codes on the tail of histone H4 from human embryonic stem (ES) cells. Finally, we quantified the abundances of these codes as human ES cells undergo differentiation to reveal striking changes in methylation and acetylation patterns. For example, H4R3 methylation was observed only in the presence of H4K20 dimethylation; such context-specific patterning exemplifies the power of this technique.

Peptide quantification using 8-plex isobaric tags and electron transfer dissociation tandem mass spectrometry

Phanstiel, D.H., Unwin, R., McAlister, G.C., Coon, J.J.   Analytical Chemistry (2009)

Isobaric tags for absolute and relative quantitation (iTRAQ) allow for simultaneous relative quantification of peptides from up to eight different samples. Typically peptides labeled with 8-plex iTRAQ tags are pooled and fragmented using beam-type collision activated dissociation (CAD) which, in addition to cleaving the peptide backbone bonds, cleaves the tag to produce reporter ions. The relative intensities of the reporters are directly proportional to the relative abundances of each peptide in the solution phase. Recently, studies using the 4-plex iTRAQ tagging reagent demonstrated that electron transfer dissociation (ETD) of 4-plex iTRAQ labeled peptides cleaves at the N-C alpha bond in the tag and allows for up to three channels of quantification. In this paper we investigate the ETD fragmentation patterns of peptides labeled with 8-plex iTRAQ tags. We demonstrate that upon ETD, peptides labeled with 8-plex iTRAQ tags fragment to produce unique reporter ions that allow for five channels of quantification. ETD-MS/MS of these labeled peptides also produces a peak at 322 m/z which, upon resonant excitation (CAD), gives rise to all eight iTRAQ reporter ions and allows for eight channels of quantification. Comparison of this method to beam-type CAD quantification shows a good correlation (y = 0.91x + 0.01, R(2) = 0.9383).

Peptide and protein quantification using iTRAQ with electron transfer dissociation

Phanstiel, D.H., Zhang, Y., Marto, J.A., Coon, J.J.   Journal of The American Society for Mass Spectrometry (2008)

Electron transfer dissociation (ETD) has become increasingly used in proteomic analyses due to its complementarity to collision-activated dissociation (CAD) and its ability to sequence peptides with post-translation modifications (PTMs). It was previously unknown, however, whether ETD would be compatible with a commonly employed quantification technique, isobaric tags for relative and absolute quantification (iTRAQ), since the fragmentation mechanisms and pathways of ETD differ significantly from CAD. We demonstrate here that ETD of iTRAQ labeled peptides produces c- and z-type fragment ions as well as reporter ions that are unique from those produced by CAD. Exact molecular formulas of product ions were determined by ETD fragmentation of iTRAQ-labeled synthetic peptides followed by high mass accuracy orbitrap mass analysis. These experiments revealed that ETD cleavage of the N-C(alpha) bond of the iTRAQ tag results in fragment ions that could be used for quantification. Synthetic peptide work demonstrates that these fragment ions provide up to three channels of quantification and that the quality is similar to that provided by beam-type CAD. Protein standards were used to evaluate peptide and protein quantification of iTRAQ labeling in conjunction with ETD, beam-type CAD, and pulsed Q dissociation (PQD) on a hybrid ion trap-orbitrap mass spectrometer. For reporter ion intensities above a certain threshold all three strategies provided reliable peptide quantification (average error <10%). Approximately 36%, 8%, and 16% of scans identified fall below this threshold for ETD, HCD, and PQD, respectively. At the protein level, average errors were 2.3%, 1.7%, and 3.6% for ETD, HCD, and PQD, respectively.