Events - Daily
|Monday, April 07|
Karen Kasza, Sloan Kettering, Spatiotemporal control of the forces that shape tissues
During embryonic development, the forces generated by myosin II must be controlled in space and time to shape simple epithelia into tissues and organs with complex form and structure. Molecular-level properties of myosin regulation and force generation have been extensively studied in vitro, but it is not understood how these molecular properties are translated to cell and tissue length scales to achieve the complex patterns of forces that shape tissues. In one dramatic example in the Drosophila melanogaster embryo, polarized patterns of myosin activity are required for oriented cell rearrangements that drive rapid doubling in tissue length along the head-to-tail axis. Our approach has been to use systematic and quantitative experimental studies to gain insight into how macroscopic tissue elongation arises from force generation at the molecular level. We have generated embryos expressing myosin variants engineered to alter specific aspects of regulation and motor function¬. For example, myosin II regulatory light chain phosphorylation promotes the assembly of myosin into active contractile filaments and controls the level of myosin activity. Surprisingly, we find that myosin variants that mimic phosphorylation accelerate cell rearrangements but alter the spatial pattern of myosin localization and force generation in the tissue, resulting in reduced tissue elongation. Our results suggest a trade-off between the speed and orientational precision of cell rearrangement and provide insight into general principles of efficient tissue remodeling.
Joseph Henry Room, Jadwin Hall · 12:00 p.m.– 1:00 p.m.
Jeffrey Leek, Johns Hopkins University, Dissecting variation in RNA-seq measurements
RNA-sequencing is the most common tool for measuring gene expression. The reasons for its popularity include dramatically reduced costs over the last 10 yeas and increased flexibility over previous technologies such as microarrays. The price for this flexibility is a much larger quantity of raw data and greater computational cost associated with quantification of expression. Dealing with this data poses for statisticians, computer scientists, and consumers of sequencing data. In this talk I will discuss computational experiments we have performed to dissect variation in sequencing experiments due to biological, technological, and developmental variation. I will also discuss variation in RNA-seq due to often overlooked sources of variability such as annotation, assembly, and bioinformatic variability. I will introduce tools my group has been developing for modeling variation at single base resolution (https://github.com/lcolladotor/derfinder) and the transcript level https://github.com/alyssafrazee/ballgown) in a range of experimental conditions. This is joint work with Alyssa Frazee, Leonardo Collado Torres, Geo Pertea, Andrew Jaffe, Ben Langmead, Rafael Irizarry, and Steven Salzberg.
Jeff Leek is an Associate Professor of Biostatistics and Oncology and Biostatistics Department Career Development Chair at the Johns Hopkins Bloomberg School of Public Health. His data analyses have focused on the molecular profiles of brain development, breast cancer, stem cell self-renewal, and the immune response to major blunt force trauma. He is the co-editor of the Simply Statistics Blog (http://simplystatistics.org/) and co-director of the Johns Hopkins Specialization in Data Science (https://www.coursera.org/specialization/jhudatascience/1). His Data Analysis course on Coursera has enrolled more than 180,000 students.
Carl Icahn Lab 101 · 4:15 p.m.– 5:15 p.m.