Gloria M. Sheynkman


Primary Appointment

Assistant Professor, Molecular Physiology and Biological Physics


  • BS, Biochemistry, University of Notre Dame
  • PhD, Chemistry, University of Wisconsin

Research Disciplines

Biochemistry, Bioinformatics and Genomics, Biophysics, Biotechnology, Cancer Biology, Cardiovascular Biology, Cell and Developmental Biology, Computational Biology, Development, Stem Cells & Regeneration, Genetics, Molecular Biology, Physiology, Statistics, Structural Biology

Research Interests

Proteoform Systems Biology: proteogenomic approaches to uncover the role of proteomic variation in human disease

Research Description

The post-genomic era is marked by the development of technologies which have revealed the astonishing molecular diversity of gene products. Multiple distinct protein forms, or âproteoformsâ, can arise through several levels of regulation from post-transcriptional mechanisms such as alternative splicing to post-translational mechanisms such as phosphorylation and proteolytic cleavage. These levels of regulation are in delicate balance to produce the set of physiologically normal proteoforms; however, disruption of this balance leads to expression of aberrant proteoforms that can underlie disease. Hence, there is an urgent need to discover all healthy and disease-associated proteoforms so as to develop the next generation of proteoform-focused biomarkers and therapies.
The Sheynkman lab seeks to understand how human proteomic variation underlies phenotypic variation, specifically to identify how proteoforms underlie human disease. Towards this end, the lab is developing new analytical and computational frameworks to study proteoform function by integrating tools and concepts from the areas of bioanalytical chemistry, network biology, and bioinformatics. We are developing approaches to reliably discover novel disease proteoforms, assay proteoform-specific functions, and elucidate the molecular mechanisms by which proteoforms rewire cellular networks to drive disease states.

Personal Statement

The post-genomic era is marked by the development of technologies which have revealed the astonishing molecular diversity of protein products. Multiple distinct protein forms, or âproteoformsâ, can be formed through post-transcriptional mechanisms such as alternative splicing and/or post-transcriptional mechanisms such as phosphorylation. The existence of so many distinct molecules being produced from the same genetic locus means we need to revise our traditional notions of the definition of a disease âgeneâ. It motivates the urgent need to enumerate all healthy and disease-associated proteoforms in human and to assess their significance â a grand challenge for todayâs era of genomic research.
At the Sheynkman Lab, we are working to found a new area of the âDisease Proteoform Systems Biologyâ, which is a systems biology approach to discover disease-driving âproteoformsâ for therapeutic intervention. To accomplish this, we are integrating a unique set of cutting-edge analytical and computational approaches from human disease genetics, genomics, proteomics, and systems and network biology. We are prototyping this approach in a disease agnostic manner to elucidate proteoform-driven rewiring events in cardiovascular disease, neurological disorders, and cancer. We believe this novel approach has massive potential to treat diseases at proteoform-resolution in this era of personalized medicine. âDisease Proteoform Systems Biologyâ is not just about our lab. We are proponents of the systems biology concept that âthe sum is greater than the partsâ. We are team science-based and we have a close network of collaborating labs to achieve our vision.

Selected Publications


Joglekar, A., Hu, W., Zhang, B., Narykov, O., Diekhans, M., Marrocco, J., . . . Tilgner, H. U. (2024). Single-cell long-read sequencing-based mapping reveals specialized splicing patterns in developing and adult mouse and human brain.. Nature neuroscience. doi:10.1038/s41593-024-01616-4

Korchak, J. A., Jeffery, E. D., Bandyopadhyay, S., Jordan, B. T., Lehe, M., Watts, E. F., . . . Sheynkman, G. M. (2024). IS-PRM-based peptide targeting informed by long-read sequencing for alternative proteome detection.. bioRxiv. doi:10.1101/2024.04.01.587549


Pardo-Palacios, F. J., Wang, D., Reese, F., Diekhans, M., Carbonell-Sala, S., Williams, B., . . . Brooks, A. N. (2023). Systematic assessment of long-read RNA-seq methods for transcript identification and quantification.. bioRxiv. doi:10.1101/2023.07.25.550582

Joglekar, A., Hu, W., Zhang, B., Narykov, O., Diekhans, M., Balacco, J., . . . Tilgner, H. U. (2023). Single-cell long-read mRNA isoform regulation is pervasive across mammalian brain regions, cell types, and development.. bioRxiv. doi:10.1101/2023.04.02.535281

Aherrahrou, R., Lue, D., Perry, R. N., Aberra, Y. T., Khan, M. D., Soh, J. Y., . . . Civelek, M. (2023). Genetic Regulation of SMC Gene Expression and Splicing Predict Causal CAD Genes. CIRCULATION RESEARCH, 132(3), 323-338. doi:10.1161/CIRCRESAHA.122.321586

Mehlferber, M. M., Kuyumcu-Martinez, M., Miller, C. L., & Sheynkman, G. M. (2023). Transcription Factors and Splice Factors-Interconnected Regulators of Stem Cell Differentiation. CURRENT STEM CELL REPORTS, 9(2), 31-41. doi:10.1007/s40778-023-00227-2

Li, M. M., Awasthi, S., Ghosh, S., Bisht, D., Coban Akdemir, Z. H., Sheynkman, G. M., . . . Yi, S. S. (2023). Gain-of-Function Variomics and Multi-omics Network Biology for Precision Medicine.. Methods in molecular biology (Clifton, N.J.), 2660, 357-372. doi:10.1007/978-1-0716-3163-8_24

Acharya, B. R., Fang, J. S., Jeffery, E., Chavkin, N. W., Genet, G., Vasavada, H., . . . Hirschi, K. K. (2023). Connexin 37 sequestering of activated-ERK in the cytoplasm promotes p27-mediated endothelial cell cycle arrest. LIFE SCIENCE ALLIANCE, 6(8). doi:10.26508/lsa.202201685

de Souza, V. B. C., Jordan, B. T. T., Tseng, E., Nelson, E. A. A., Hirschi, K. K. K., Sheynkman, G., & Robinson, M. D. D. (2023). Transformation of alignment files improves performance of variant callers for long-read RNA sequencing data. GENOME BIOLOGY, 24(1). doi:10.1186/s13059-023-02923-y

Abood, A., Mesner, L., Jeffery, E., Murali, M., Lehe, M., Saquing, J., . . . Sheynkman, G. (2023). Long-read proteogenomics to connect disease-associated sQTLs to the protein isoform effectors of disease. doi:10.1101/2023.03.17.531557

Pan, X., Akdemir, Z. H. C., Gao, R., Jiang, X., Sheynkman, G. M., Wu, E., . . . Yi, S. S. (2023). AD-Syn-Net: systematic identification of Alzheimer's disease-associated mutation and co-mutation vulnerabilities via deep learning. BRIEFINGS IN BIOINFORMATICS, 24(2). doi:10.1093/bib/bbad030


Chavkin, N. W., Genet, G., Poulet, M., Jeffery, E. D., Marziano, C., Genet, N., . . . Hirschi, K. K. (2022). Endothelial cell cycle state determines propensity for arterial-venous fate. NATURE COMMUNICATIONS, 13(1). doi:10.1038/s41467-022-33324-7

Castaldi, P. J., Abood, A., Farber, C. R., & Sheynkman, G. M. (2022). Bridging the splicing gap in human genetics with long-read RNA sequencing: finding the protein isoform drivers of disease. HUMAN MOLECULAR GENETICS, 31(R1), R123-R136. doi:10.1093/hmg/ddac196

Mehlferber, M. M., Jeffery, E. D., Saquing, J., Jordan, B. T., Sheynkman, L., Murali, M., . . . Sheynkman, G. M. (2022). Characterization of protein isoform diversity in human umbilical vein endothelial cells via long-read proteogenomics. RNA BIOLOGY, 19(1), 1228-1243. doi:10.1080/15476286.2022.2141938

de Crecy-Lagard, V., de Hegedus, R. A., Arighi, C., Babor, J., Bateman, A., Blaby, I., . . . Xu, J. (2022). A roadmap for the functional annotation of protein families: a community perspective. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION, 2022. doi:10.1093/database/baac062

Miller, R. M., Jordan, B. T., Mehlferber, M. M., Jeffery, E. D., Chatzipantsiou, C., Kaur, S., . . . Sheynkman, G. M. (2022). Enhanced protein isoform characterization through long-read proteogenomics. GENOME BIOLOGY, 23(1). doi:10.1186/s13059-022-02624-y

Martin, W., Sheynkman, G., Lightstone, F. C., Nussinov, R., & Cheng, F. (2022). Interpretable artificial intelligence and exascale molecular dynamics simulations to reveal kinetics: Applications to Alzheimer's disease. CURRENT OPINION IN STRUCTURAL BIOLOGY, 72, 103-113. doi:10.1016/


Leung, S. K., Jeffries, A. R., Castanho, I., Jordan, B. T., Moore, K., Davies, J. P., . . . Mill, J. (2021). Full-length transcript sequencing of human and mouse cerebral cortex identifies widespread isoform diversity and alternative splicing. CELL REPORTS, 37(7). doi:10.1016/j.celrep.2021.110022


Saferali, A., Xu, Z., Sheynkman, G. M., Hersh, C. P., Cho, M. H., Silverman, E. K., . . . Castaldi, P. J. (2020). Characterization of a COPD-Associated NPNT Functional Splicing Genetic Variant in Human Lung Tissue via Long-Read Sequencing.. medRxiv. doi:10.1101/2020.10.20.20203927

Sheynkman, G. M., Tuttle, K. S., Laval, F., Tseng, E., Underwood, J. G., Yu, L., . . . Vidal, M. (2020). ORF Capture-Seq as a versatile method for targeted identification of full-length isoforms. NATURE COMMUNICATIONS, 11(1). doi:10.1038/s41467-020-16174-z

Luck, K., Kim, D. -K., Lambourne, L., Spirohn, K., Begg, B. E., Bian, W., . . . Calderwood, M. A. (2020). A reference map of the human binary protein interactome. NATURE, 580(7803), 402-+. doi:10.1038/s41586-020-2188-x


Schmidt, K., Carroll, J. S., Yee, E., Thomas, D. D., Wert-Lamas, L., Neier, S. C., . . . Novina, C. D. (2019). The lncRNA SLNCR Recruits the Androgen Receptor to EGR1-Bound Genes in Melanoma and Inhibits Expression of Tumor Suppressor p21. CELL REPORTS, 27(8), 2493-+. doi:10.1016/j.celrep.2019.04.101

Miller, R. M., Millikin, R. J., Hoffmann, C. V., Solntsev, S. K., Sheynkman, G. M., Shortreed, M. R., & Smith, L. M. (2019). Improved Protein Inference from Multiple Protease Bottom-Up Mass Spectrometry Data. JOURNAL OF PROTEOME RESEARCH, 18(9), 3429-3438. doi:10.1021/acs.jproteome.9b00330


Anvar, S. Y., Allard, G., Tseng, E., Sheynkman, G. M., de Klerk, E., Vermaat, M., . . . 't Hoen, P. A. C. (2018). Full-length mRNA sequencing uncovers a widespread coupling between transcription initiation and mRNA processing. GENOME BIOLOGY, 19. doi:10.1186/s13059-018-1418-0


Luck, K., Sheynkman, G. M., Zhang, I., & Vidal, M. (2017). Proteome-Scale Human Interactomics. TRENDS IN BIOCHEMICAL SCIENCES, 42(5), 342-354. doi:10.1016/j.tibs.2017.02.006


Sheynkman, G. M., Shortreed, M. R., Cesnik, A. J., & Smith, L. M. (2016). Proteogenomics: Integrating Next-Generation Sequencing and Mass Spectrometry to Characterize Human Proteomic Variation. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY, VOL 9, 9, 521-545. doi:10.1146/annurev-anchem-071015-041722

Yang, X., Coulombe-Huntington, J., Kang, S., Sheynkman, G. M., Hao, T., Richardson, A., . . . Vidal, M. (2016). Widespread Expansion of Protein Interaction Capabilities by Alternative Splicing. CELL, 164(4), 805-817. doi:10.1016/j.cell.2016.01.029

Cesnik, A. J., Shortreed, M. R., Sheynkman, G. M., Frey, B. L., & Smith, L. M. (2016). Human Proteomic Variation Revealed by Combining RNA-Seq Proteogenomics and Global Post-Translational Modification (G-PTM) Search Strategy. JOURNAL OF PROTEOME RESEARCH, 15(3), 800-808. doi:10.1021/acs.jproteome.5b00817

Keller, M. P., Paul, P. K., Rabaglia, M. E., Stapleton, D. S., Schueler, K. L., Broman, A. T., . . . Attie, A. D. (2016). The Transcription Factor Nfatc2 Regulates β-Cell Proliferation and Genes Associated with Type 2 Diabetes in Mouse and Human Islets. PLOS GENETICS, 12(12). doi:10.1371/journal.pgen.1006466


Shortreed, M. R., Wenger, C. D., Frey, B. L., Sheynkman, G. M., Scalf, M., Keller, M. P., . . . Smith, L. M. (2015). Global Identification of Protein Post-translational Modifications in a Single-Pass Database Search. JOURNAL OF PROTEOME RESEARCH, 14(11), 4714-4720. doi:10.1021/acs.jproteome.5b00599


Sheynkman, G. M., Johnson, J. E., Jagtap, P. D., Shortreed, M. R., Onsongo, G., Frey, B. L., . . . Smith, L. M. (2014). Using Galaxy-P to leverage RNA-Seq for the discovery of novel protein variations. BMC GENOMICS, 15. doi:10.1186/1471-2164-15-703

Wen, B., Xu, S., Sheynkman, G. M., Feng, Q., Lin, L., Wang, Q., . . . Liu, S. (2014). sapFinder: an R/Bioconductor package for detection of variant peptides in shotgun proteomics experiments. BIOINFORMATICS, 30(21), 3136-3138. doi:10.1093/bioinformatics/btu397


Sheynkman, G. M., Shortreed, M. R., Frey, B. L., Scalf, M., & Smith, L. M. (2014). Large-Scale Mass Spectrometric Detection of Variant Peptides Resulting from Nonsynonymous Nucleotide Differences. JOURNAL OF PROTEOME RESEARCH, 13(1), 228-240. doi:10.1021/pr4009207

Sheynkman, G. M., Shortreed, M. R., Frey, B. L., & Smith, L. M. (2013). Discovery and Mass Spectrometric Analysis of Novel Splice-junction Peptides Using RNA-Seq. MOLECULAR & CELLULAR PROTEOMICS, 12(8), 2341-2353. doi:10.1074/mcp.O113.028142


Sturm, R., Sheynkman, G., Booth, C., Smith, L. M., Pedersen, J. A., & Li, L. (2012). Absolute Quantification of Prion Protein (90-231) Using Stable Isotope-Labeled Chymotryptic Peptide Standards in a LC-MRM AQUA Workflow. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY, 23(9), 1522-1533. doi:10.1007/s13361-012-0411-1


Wu, C. -H., Chen, S., Shortreed, M. R., Kreitinger, G. M., Yuan, Y., Frey, B. L., . . . Smith, L. M. (2011). Sequence-Specific Capture of Protein-DNA Complexes for Mass Spectrometric Protein Identification. PLOS ONE, 6(10). doi:10.1371/journal.pone.0026217


Kulevich, S. E., Frey, B. L., Kreitinger, G., & Smith, L. M. (2010). Alkylating Tryptic Peptides to Enhance Electrospray Ionization Mass Spectrometry Analysis. ANALYTICAL CHEMISTRY, 82(24), 10135-10142. doi:10.1021/ac1019792