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Large retinal ganglion cells in the pipid frog Xenopus laevis form independent, regular mosaics resembling those of teleost fishes
Published online by Cambridge University Press: 02 June 2009
Abstract
Population-based studies of retinal neurons have helped to reveal their natural types in mammals and teleost fishes. In this, the first such study in a frog, labeled ganglion cells of the mesobatrachian Xenopus laevis were examined in flatmounts. Cells with large somata and thick dendrites could be divided into three mosaic-forming types, each with its own characteristic stratification pattern. These are named αa, αab, and αc, following a scheme recently used for teleosts. Cells of the αa mosaic (~0.4% of all ganglion cells) had very large somata and trees, arborizing diffusely within sublamina a (the most sclerad). Their distal dendrites were sparsely branched but achieved consistent coverage by intersecting those of their neighbors. Displaced and orthotopic cells belonged to the same mosaic, as did cells with symmetric and asymmetric trees. Cells of the αab mosaic (~1.2%) had large somata, somewhat smaller trees that appeared bistratified at low magnification, and dendrites that branched extensively. Their distal dendrites arborized throughout sublamina b and the vitread part of a, tessellating with their neighbors. All were orthotopic; most were symmetric. Cells of the αc mosaic (~0.5%) had large somata and very large, sparse, flat, overlapping trees, predominantly in sublamina c. All were orthotopic; some were asymmetric. Nearest-neighbor analyses and spatial correlograms confirmed that each mosaic was regular and independent, and that spacings were reduced in juvenile frogs. Densities, proportions, sizes, and mosaic statistics are tabulated for all three types, which are compared with types defined previously by size and symmetry in Xenopus and potentially homologous mosaic-forming types in teleosts. Our results reveal strong organizational similarities between the large ganglion cells of teleosts and frogs. They also demonstrate the value of introducing mosaic analysis at an early stage to help identify characters that are useful markers for natural types and that distinguish between within-type and between-type variation in neuronal populations.
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