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Nicola de Prisco, Fabiola Curion, Salvatore Botta, Elena Marrocco, Martina Sofia, Sandro Banfi, Carlo Gesualdo, Settimio Rossi, Francesca Simonelli, Enrico Maria Surace; WITHDRAWN - Transcriptional landscape of porcine rod and cone photoreceptors. Invest. Ophthalmol. Vis. Sci. 2018;59(9):3095.
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Differentiated rod and cone photoreceptors display similar phenotypic features to capture and transduce light stimuli from the natural scene. However, rods and cones show specific light response properties. Here we investigated their transcriptome identities by RNA-sequencing (RNA-seq) in the porcine retina.
We developed an Adeno-associated viral (AAV) vector carrying two independent expression cassettes (“Double Fluo”) enabling specific somatic labeling of rods and cones of the porcine retina. We performed RNA-sequencing on FACS sorted single cell populations and curried out differential expression gene (DEG) analysis. In addition, we performed RNA-sequencing and generated a co-expression network on the whole retina from 47 samples (SusNet). Finally, we cross compared the DEGs on the SusNet co-expression network.
We identified porcine genes expressed throughout the retina and in rod and cone cell-specific populations. Cross comparison between whole retina and sorted rod and cone transcriptomes enabled the identification of Gene Regulatory Networks (GRN) operating at tissue and cell-specific levels. In particular, we identified transcription factors (TFs) exclusively expressed in rods and in cones and their in silico hierarchical mode of function. Furthermore, cross mapping of cone and rod specific DEGs on SusNet co-expression network enabled to further reconstruct their spatial transcriptomes pattern domains and their derived identities.
We generated RNA-sequencing data sets of retinal and photoreceptors transcriptomes from porcine retina. We generated a co-expression network (SusNet) and reconstructed rod and cone specific GRN, thus providing an important framework and resource to get into retinal gene regulatory properties.
This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.
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