Many biological experiments are performed on groups of cells, under the assumption that all cells of a particular “type” are identical. However, recent evidence from studies of single cells reveals that this assumption is incorrect. Individual cells within the same population may differ dramatically, and these differences can have important consequences for the health and function of the entire population.
Single Cell Analysis Program Data Portal
Single cell transcriptomic protocols and data generated by the Single Cell Analysis Program-Transcriptome (SCAP-T) project can be accessed via the data portal or dbGaP study page. These resources include phenotypic information and next generation sequencing data of the whole transcriptome for nearly 700 single cells from the human brain and heart.
Phase 2 of the Follow that Cell Challenge is underway and is only open to Phase 1 finalists. During Phase 2, Reduction to Practice, finalists will generate proof-of-concept data related to their Phase 1 entries. Submissions are due March 30, 2017.
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NEW! Related Funding Opportunities for Pilot Projects for a Human Cell Atlas. The Human Cell Atlas is a global effort to create a reference map of all cells in the healthy human body as a resource for studies of health and disease. The Chan Zuckerberg Initiative invites applications for one year pilot projects to develop technologies for the Human Cell Atlas, establish best practices in the field, and begin a common data archive for analysis and investigation. Applications are due April 17, 2017. Full details here.
NEW! The Common Fund Single Cell Analysis Program (SCAP) will host its 5th and final Annual Investigators Meeting on June 29 - 30, 2017, at the Clinical Center on the NIH campus in Bethesda, Maryland. The purpose of the SCAP is to accelerate the discovery, development, and translation of cross-cutting, innovative approaches to analyzing the heterogeneity of biologically relevant populations of cells in situ. Register and learn more about this meeting here.
Related Funding Opportunities for Single Cell Analysis tools and technology development. Learn more about these opportunities here: Development of Highly Innovative Tools and Technology for Analysis of Single Cells (STTR) (R41/R42), Development of Highly Innovative Tools and Technology for Analysis of Single Cells (SBIR) (R43/R44).
New Single Cell System for Studying Live Human Brain Cells
A team of scientists, led by Single Cell Analysis Program investigator Dr. James Eberwine, have developed a new system for studying live human brain cells donated from neurosurgery, which will help researchers understand human brain diseases and how to treat them. Read the full story here.
Single cell analysis at the threshold. In an interview with Nature Methods, Single Cell Analysis Program grantee Dr. Nicholas Navin and experts discuss insights into some of the challenges and promises of single-cell technology. Learn more here.
Spatial Complexity of the Mouse Hippocampus Resolved
Toward new approaches to study the spatial organization of tissues at single cell resolution, Single Cell Analysis grantee Dr. Long Cai, identified unique gene expression states in the mouse hippocampus, by quantifying and clustering 249 genes in 16,958 cells. This was accomplished using sequential barcoded fluorescence in situ hybridization (seqFISH), a technique that correlates the spatial expression of different genes in the same cell without removing cells from their original location within tissue. Using seqFISH, the authors report resolving the structural organization of the mouse hippocampus with unprecedented single cell resolution. Read the full story here.
Congratulations to Dr. Bo Huang, a Single Cell Analysis Program grantee awarded the 2016 American Society for Cell Biology Early Career Life Scientist Award. Dr. Huang's innovation in microscopy includes new algorithms for improving super-resolution microscopy, repurposing nanobodies for studying G protein-coupled receptor signaling, and retooling CRISPR/Cas9 for visualizing genome organization in real time. Read more about this award here.