Biology subjects

Stamatoyannopoulos, J. A.

Publications and source records attributed to Stamatoyannopoulos, J. A..

3 recordsLinked to original sources

bioRxiv2018

Quantification of nuclear protein dynamics reveals chromatin remodeling during acute protein degradation

Sequencing-based technologies cannot measure post-transcriptional dynamics of the nuclear proteome, but unbiased mass-spectrometry measurements of chromatin-associated proteins remain difficult. In this work, we have combined facile nuclear sub-fractionation approaches with data-independent acquisition mass spectrometry to improve detection and quantification of nuclear proteins in human cells and tissues. Nuclei are isolated and subjected to a series of extraction conditions that enrich for nucleoplasm, euchromatin, heterochromatin and nuclear-membrane associated proteins. Using this approach, we can measure peptides from over 70% of the expressed nuclear proteome. As we are physically separating chromatin compartments prior to analysis, proteins can be assigned into functional chromatin environments to illuminate systems-wide nuclear protein dynamics. The integrity of nuclear sub-compartments were validated with immunofluorescence, which confirms the presence of key markers during chromatin extraction. We then apply this method to study the nuclear proteome-wide response to pharmacological degradation of the BET bromodomain proteins. BET degradation leads to widespread changes in chromatin composition, and we discover global HDAC1/2-mediated remodeling of chromatin previously bound by BET bromodomains. In summary, we have developed a technology for reproducible, comprehensive characterization of the nuclear proteome to observe the systems-wide nuclear protein dynamics.

systems biology↗

bioRxiv2018

Mapping and dynamics of regulatory DNA during seed development

The genome is reprogrammed during development to produce diverse cell types, largely through altered expression and activity of key transcription factors. The accessibility and critical functions of epidermal cells have made them a model for connecting transcriptional events to development in a range of model systems. In Arabidopsis thaliana and many other plants, fertilization triggers differentiation of specialized epidermal seed coat cells that have a unique morphology caused by large extracellular deposits of pectin. Here, we used DNase I-seq to generate regulatory landscapes of A. thaliana seeds at two critical time points in seed coat maturation, enriching for seed coat cells with the INTACT method. We found over 3000 developmentally dynamic regulatory DNA elements and explored their relationship with nearby gene expression. The dynamic regulatory elements were enriched for motifs for several transcription factors families; most notably the TCP family at the earlier time point and the MYB family at the later one. To assess the extent to which the observed regulatory sites in seeds added to previously known regulatory sites in A. thaliana, we compared our data to 11 other data sets generated with seven-day-old seedlings for diverse tissues and conditions. Surprisingly, over a quarter of the regulatory, i.e. accessible, bases observed in seeds were novel. Notably, in this comparison, development exerted a stronger effect on the plant regulatory landscape than extreme environmental perturbations, highlighting the importance of extending studies of regulatory landscapes to other tissues and cell types during development.

plant biology↗

bioRxiv2017

An Integrative Framework For Detecting Structural Variations In Cancer Genomes

Structural variants can contribute to oncogenesis through a variety of mechanisms, yet, despite their importance, the identification of structural variants in cancer genomes remains challenging. Here, we present an integrative framework for comprehensively identifying structural variation in cancer genomes. For the first time, we apply next-generation optical mapping, high-throughput chromosome conformation capture (Hi-C), and whole genome sequencing to systematically detect SVs in a variety of cancer cells.\n\nUsing this approach, we identify and characterize structural variants in up to 29 commonly used normal and cancer cell lines. We find that each method has unique strengths in identifying different classes of structural variants and at different scales, suggesting that integrative approaches are likely the only way to comprehensively identify structural variants in the genome. Studying the impact of the structural variants in cancer cell lines, we identify widespread structural variation events affecting the functions of non-coding sequences in the genome, including the deletion of distal regulatory sequences, alteration of DNA replication timing, and the creation of novel 3D chromatin structural domains.\n\nThese results underscore the importance of comprehensive structural variant identification and indicate that non-coding structural variation may be an underappreciated mutational process in cancer genomes.

genomics↗