Phenotypic map of porcine retinal ganglion cells

Research output: Contribution to journalArticle


PURPOSE: Porcine retina is an excellent model for studying diverse retinal processes and diseases. The morphologies of porcine retinal ganglion cells (RGCs) have, however, not yet been described comprehensively. The aim of the present study was to créate a classification of the RGCs using the 1, 1'-dioctadecyl-3,3,3',3'-tetramethylindocarbocyanine perchlorate (DiI) tracing method.

METHODS: About 170 RGCs were retrogradely labeled by injecting DiI into the optic nerve of postmortem eyes and statistically analyzed by two different clustering methods: Ward's algorithm and the K-means clustering. Major axis length of the soma, soma area size, and dendritic field area size were selected as main parameters for cluster classification.

RESULTS: RGC distribution in clusters was achieved according to their morphological parameters. It was feasible to combine both statistical methods, thereby obtaining a robust clustering distribution. Morphological analysis resulted in a classification of RGCs in three groups according to the soma size and dendritic field: A (large somas and large dendritic fields), B (medium to large somas and medium to large dendritic fields), C (medium to small somas and medium to small dendritic fields). Within groups, fine clustering defined several subgroups according to dendritic arborization and level of stratification. Additionally, cells stratifying in two different levels of the inner plexiform layer were observed within the clusters.

CONCLUSIONS: This comprehensive study of RGC morphologies in the porcine retina provides fundamental knowledge about RGC cell types and provides a basis for functional studies toward selective RGC cell degeneration in retinal disorders.


External organisations
  • University of the Basque Country
Research areas and keywords


  • Animals, Cell Count, Cell Size, Cluster Analysis, Dendrites, Models, Biological, Phenotype, Retinal Ganglion Cells, Sus scrofa, Journal Article, Research Support, Non-U.S. Gov't
Original languageEnglish
Pages (from-to)904-16
Number of pages13
JournalMolecular Vision
Publication statusPublished - 2013
Publication categoryResearch
Externally publishedYes