Center for Genome Imaging (CGI)
The goal of the CGI is to develop, implement, and disseminate imaging, analysis, and modeling technologies that will elucidate how genomes, in their entirety, are organized and function in three dimensions (3D).
Develop strategies to massively scale imaging methods.
Develop strategies for distinguishing maternal and paternal homologs as well as visualizing repeated sequences.
Produce computational pipelines to increase the power and speed of image analysis and genome 3D modeling.
Support the community through a CGI incubator, internships, and courses.
Jumana AlHaj Abed
I want to understand the relationship between homologous chromosome shapes, epigenetic marks, and transcriptional programs in extreme scenarios using homolog-specific super-resolution imaging and chromatin conformation capture technologies. In Drosophila, homologous pairing events are genome-wide, abundant, and extensive and, in mammals, they are rare and stochastic. What are the common or different principles governing functional trans-homologous contact events in different contexts and organisms?
Imaging the structural organization of the whole human genome is an adventure. Being able to visualize with nanometer resolution this information-rich origami masterpiece is daunting, especially if you take it one molecule localization at a time. I’m thankful for being in the midst of what I would call an expedition team, which is joining forces of biological conceptualization, photo-physical finesse, and computational analytics. Let’s climb this mountain!
Ivan Bochkov is a graduate student in the Department of Genetics & Genomics at Baylor College of Medicine. He has expertise in performing both sequencing-based and microscopy-based methods for probing 3D genome architecture. He will contribute to the project by developing and scaling up these methods to the whole-genome level.
Laura is a biochemist with a background in gene regulation, microscopy and image analysis. She is interested in understanding whole-genome organization in health and disease using diffraction-limited and super-resolution microscopy. For this goal, she also works on new imaging technologies and image analysis methods.
David Castillo obtained his MSc in Photonics from the Universitat Politècnica de Catalunya in Barcelona (Spain) where he worked in Super-resolution microscopy. He has a background in Physics and Engineering. He works as a bioinformatics technician in the Structural Genomics team of Marc A. Martí-Renom at CNAG-CRG (Barcelona), developing tools for the analysis, modelling and visualization of HiC data. He is also interested in the integration of microscopy to the modeling of genomic 3D structures.
Audrey Dalgarno in PhD candidate in the Neretti lab at Brown University in the Molecular Biology, Cell Biology, and Biochemistry program. Her research focuses on the role of genomic architecture in cellular senescence. For her project, she will combine spatial multi-omic microscopy with machine learning to determine the ability of local chromatin structure to predict transcriptional status at senescence-associated loci.
Olga Dudchenko has extensive experience with data analysis involving Hi-C, a method for probing the 3D structure of genomes through proximity ligation and high-throughput sequencing, specifically those involving genome assembly, phasing and structural rearrangement analysis. She is the author of several widely used bioinformatics tools for Hi-C based genome assembly including 3D-DNA, the pipeline for automatic assembly of chromosomes using Hi-C data, and Juicebox Assembly Tools or JBAT, an interactive tools for manual polishing of genome assemblies. She will contribute, among other efforts, to creating new tools and computational pipelines that utilize 3D imaging for structural variability and extended homolog resolution.
Over the years, as a computational structural biologist, I have leveraged the integration of experimental data (mainly obtained using imaging techniques) and computational methods to learn more about the mechanisms by which chromatin is organized within nuclei. My goal is to develop and apply transformative tools for the genome-wide analysis and modelling of super-resolution genome images. This will significantly facilitate the investigation of spatial genome organization at an unprecedented scale and resolution.
Being a computational knot theorist, I am interested in understanding the topology of genomes from a mathematical point of view. Are there any mathematical/topological mechanisms that drive their organization in 3D-space? If yes, how are they relevant to biology? These are some of the questions that drive my research. Currently, I am focused on applying imaging methods like OligoSTORM to visualize genomes and then using original mathematical and computational methods to infer their topology.
Coming from a background in centromere biology, chromosome segregation, and genome instability, I am interested in visualizing the genome-wide structural arrangement of chromosomes in order to understand how structure impacts genome integrity. To this end, I am utilizing OligoFISSEQ and developing new imaging methods in cells as well as in tissues and organisms.
Jeremy Horrell is a PhD candidate in the Neretti laboratory as part of the Molecular Biology, Cell Biology, and Biochemistry Graduate Program at Brown University. His research interests center around interrogating the hierarchical nature of chromosome architecture of normal and aging human genomes through the combined use of Oligopaints, diffraction-limited, and super-resolution microscopy.
Super resolution imaging techniques, such as OligoSTORM and OligoDNA-PAINT developed by the Wu lab, have enabled us to address many problems in the biomedical field. However, analyzing a large amount of 3D chromosome imaging data is a big challenge. With a background in data/image processing and analysis and machine learning, my mission in this team is to leverage my knowledge and skills to overcome these challenges. My research will be mainly focused on: 1) investigating state of the art methods to discover the patterns and mechanisms implicated in 3D chromosome imaging data; 2) building predictive models using machine/deep learning to help diagnose and treat various kinds of diseases and improve human health.
S. Dean Lee
I am interested in the structural interplay between the maternal and paternal genomes in diploid organisms. To that end, I am developing a genome-wide imaging technology to identify the maternal and paternal chromosomes at conventional as well as super resolution. Integrating images representing both resolutions, I seek to elucidate the potential implications of intracellular variability in chromatin packaging between the maternal and paternal chromosomes.
Understanding the vastness of information behind genome organization that leads to cell function is what drives my research. Thus, I am actively developing and implementing new imaging and computational tools to tackle this gigantic effort of imaging whole genomes.
I apply the technologies of Oligopaints and OligoSTORM to the development of experimental pipelines for tackling biological questions at the level of the chromosome. This goal has led me to develop tools such as MART (Multiple-Alignment Repeat-Targeting) probes. The focus of my work has been on complex genomic regions, such as centromeres, on which the inheritance of entire genomes rests.
I am a PhD student in the Structural Genomics group at CNAG-CRG. My research is focused on the identification of differential "3D enhancer hubs" in organoids derived from colorectal cancer patients, with respect to healthy tissue. To get a detailed picture of the genes involved in colorectal cancer, we will combine computational modelling with Next-Generation Sequencing technologies, and we will further adapt the newly developed imaging methods OligoFISSEQ and OligoSTORM to visualize the entire genome on organoids.
Donald Olins is a Visiting Scientist in Erez’s group and a Research Professor at the University of New England. His principal research interest is the 3-D structure of chromatin and nuclei from the perspective of a cell biologist. Major research pleasures include cell culture, immunostaining and immunoblotting of nuclear antigens. Current research projects include myeloid cell differentiation; the role of LBR in nuclear shape; the structure of interphase epichromatin (i.e., chromatin adjacent to the nuclear envelope).
Ada Olins is a Visiting Scientist in Erez’s group and a Research Professor at the University of New England. Her preferred research tool is the microscope with strong interests in the 3-D structure of chromatin and nuclei. Confocal imaging of the immunostained preparations, deconvolution and analysis in 2- and 3-D are routine. The role of LBR in nuclear shape, the surface of interphase nuclei (epichromatin) and macrophage differentiation are current subjects of investigation.
Azucena Rocha is a PhD candidate in the Molecular and Cellular Biology program at Brown University. Her research focuses on investigating the association of cyclic GMP-AMP synthase (cGAS) with repetitive elements in the nucleus, with a particular interest in cellular senescence and aging.
Ultraconserved elements (UCEs) are a set of DNA sequences that are identical across distantly related genomes. Scattered across the entire genome and unique, UCEs have been conserved for over 300 million years. However, the role of UCEs in the genome is still unclear. My work focuses on understanding ultraconservation and its function in the genome via imaging and CRISPR-based editing.
As a physicist by training, I took the turn toward biology during my PhD developing both tools and instrumentation for DNA-based super-resolution microscopy (SR). I will be bringing my SR-background in DNA-PAINT to the CGI as we work toward imaging entire genomes at the single-cell level.
Douglass Turner is a software developer. He has over 15 years of experience in software development services for data visualization and 3D graphics. He specializes in front-end Web Development, software development, and training services. He will work on the spacewalk system for microscopy data visualization.
David Weisz is a computer scientist in the Aiden lab with expertise in Hi-C data flows, cloud computing, and high performance computation (HPC). His wok in the lab focuses on the development of pipelines, adapting and optimizing them to HPC Clusters, monitoring and analysis of data. Within the Center for Genome Imaging (CGI) CEGS project he will be able to contribute by using the extensive experience with technologies in the computational field of bioinformatics.
My research interest is to use OligoSTORM and OligoFISSEQ to achieve whole genome imaging in super resolution. With a background in chemistry and microscopy, I am hoping also to contribute to the development of new technologies, from fluidics to imaging.