Marissa-Macchieto

Ricardo Ramirez

Ph.D. Student

ricardnr@uci.edu

Research Interests:

I have always been interested in understanding the mechanics of how developmental programs control cell fate. The focus of my work is to understand how the Cis-regulatory modules encoded in the genome and chromatin architecture are coordinated to control gene regulatory circuits in various mammalian developmental systems, using genome-wide sequencing approaches.



Projects:

The HL-60 human promyelocytic leukemia cell line can reproducibly be terminally differentiated into distinct myeloid lineages which include macrophages, neutrophils, and monocytes over the course of several days, and for which a wealth of information is available. In an effort to understand the dynamics of cell-fate commitment and differentiation, I have utilized DNase-seq/ATAC-seq in high-resolution time courses of differentiation of HL-60 cells into neutrophil, macrophage, and monocyte lineages to understand which CRMs are activated or repressed, and track changes of protein-DNA footprints as cells irreversibly differentiate. While tracking the accessibility of CRMs, I have also measured transcriptome dynamics (RNA-seq), miRNA expression (Nanostring), transcriptional regulation of specific-key factors (ChIP-seq), and chromatin long-range interactions (ChIA-PET) during differentiation of multiple granulocyte lineages. Thus, by combining multiple next-generation sequencing data, followed by extensive validation using genome-editing approaches, I hope to generate functional and predictive networks, allowing for a comprehensive genome-wide understanding of cellular commitment.

The STATegra project aims to develop new statistical methods and tools for the integrative analysis of diverse omics data for a more efficient use of the genomics technologies. The approach involves a pre-B cell line, B3, and an inducible version of the Ikaros transcription factor, Ikaros-ERt2. STATegra has collected next-generation sequencing data using 8 biochemical assays, totaling 560 datasets across 6 time-points. I have contributed to the STATegra project in the generation and computational analysis of DNase-seq, single-cell RNA-seq, and single-cell ATAC-seq data during pre-B cell differentiation.

Other Interests:

Aside from bench work and data analysis, I enjoy playing guitar, listening to music, hiking, playing soccer and rock climbing.