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S Scott Whitmore, Adam P DeLuca, Luke A Wiley, Erin R Burnight, Miles J Flamme-Wiese, Budd A Tucker, Robert F Mullins, Todd E Scheetz, Edwin M Stone; Assessing transcriptional diversity of human and mouse photoreceptor cells by single-cell RNA-Seq. Invest. Ophthalmol. Vis. Sci. 2016;57(12):4795.
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© ARVO (1962-2015); The Authors (2016-present)
Normal vision depends upon biological variation within photoreceptor cell populations, most strikingly between rods and cones but also reflected by the morphological distinction between foveal and extrafoveal cones. However, we know little about the molecular diversity of these cell populations. In order to gain new insights into the molecular heterogeneity of different photoreceptor cells, we performed single-cell RNA sequencing (RNA-Seq) on human and mouse retinas using the Fluidigm C1 system.
In the first experiment, a single 8 mm punch of neural retina was taken from the macula of an 84 year old male human donor with normal ocular history. Tissue was dissociated in dispase and processed on the Fluidigm C1 single-cell capture system. In the second experiment, two retinas from a single C57BL/6 mouse were dissected. Cells were dissociated in dispase, pooled, and processed on the C1 system. cDNAs and libraries were generated according to Fluidigm's recommended protocol. For each experiment, double-barcoded cell libraries were pooled and sequenced on a single lane of the Illumina HiSeq 2500 platform. Sequence reads were trimmed to remove adapters, mapped to either the mm10 or hg19 genome, and counted per gene.
For the human experiment, a total of 20 single-cell capture sites on the C1 chip showed robust transcriptome profiles across 123 genes. Network analysis using the STRING database tool assigned the majority of these genes to one of three clusters, enriched for phototransduction (e.g., RHO, SAG), transcription/translation (e.g., EIF1, POLR2B) or metabolism (e.g., NDUFA4, COX7C). At least 24 of these genes have previously been implicated in retinal disease. Likewise, for the mouse experiment, we identified a total of 21 capture sites with robust expression of 83 genes. STRING analysis revealed a network substructure similar to that observed for the human data.
We plan to use our growing database of single-cell transcriptomes to improve the therapeutic potential of our iPSC-derived photoreceptor cells. By comparing expression patterns between genes, our analysis suggests several novel candidate disease genes. In future experiments, we will separately profile foveal and extrafoveal cones, to tailor differentiation protocols for cones most like those lost in AMD and other macular diseases.
This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.
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