Cited by 7.8kOpen Access
Harvard University
Publishes on Retinal Development and Disorders, Cell Image Analysis Techniques, Circadian rhythm and melatonin. 4 papers and 8.2k citations.
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Understanding how >30 types of retinal ganglion cells (RGCs) in the mouse retina each contribute to visual processing in the brain will require more tools that label and manipulate specific RGCs. We screened and analyzed retinal expression of Cre recombinase using 88 transgenic driver lines. In many lines, Cre was expressed in multiple RGC types and retinal cell classes, but several exhibited more selective expression. We comprehensively mapped central projections from RGCs labeled in 26 Cre lines using viral tracers, high-throughput imaging, and a data processing pipeline. We identified over 50 retinorecipient regions and present a quantitative retina-to-brain connectivity map, enabling comparisons of target-specificity across lines. Projections to two major central targets were notably correlated: RGCs projecting to the outer shell or core regions of the lateral geniculate projected to superficial or deep layers within the superior colliculus, respectively. Retinal images and projection data are available online at http://connectivity.brain-map.org.
Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-seq, a strategy for quickly profiling thousands of individual cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cells RNAs, and sequencing them all together. Drop-seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts cell of origin. We analyzed transcriptomes from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution. VIDEO ABSTRACT.