Birds have exceptionally sharp vision, facilitated by the retina, a specialised neural tissue in the eye involved in photoreception and -transduction.
In addition, the bird is unique in its lack of internal blood vessels, a key characteristic of neural tissues in other endothermic animals.
Thus, the bird retina represents a key tissue for understanding mechanisms associated with visual function and metabolic physiology.
The bird retina is housed within the bird eye, confined within the scleral connective tissue and the choroid behind the retina, and
the vitreous and cornea on the light-facing side of the retina. Within the vitreous, a vascular structure called the pecten oculi is involved in supplying nutrients to the retina.
The ZeFiRST database allows researchers to explore gene expression of the zebra finch retina in individual cell types (single cell transcriptomics) and spatial gene expression in the entire eye (spatial transcriptomics).
Please cite the database as:
Citation will be updated.
Type gene symbol for gene of interest for spatial plot
Spot information / gene expression violin plot / box plot
in this section, users can visualise the gene expression or continuous Spot information
(e.g. Number of UMIs / module score) across groups of Spots (e.g. libary / clusters).
in this section, users can visualise the gene expression patterns of
multiple genes grouped by categorical Spot information (e.g. library / cluster).
The normalised expression are averaged, log-transformed and then plotted.
Cell information / gene expression violin plot / box plot
In this tab, users can visualise the gene expression or continuous cell information
(e.g. Number of UMIs / module score) across groups of cells (e.g. libary / clusters).
Proportion / cell numbers across different cell information
In this tab, users can visualise the composition of single cells based on one discrete
cell information across another discrete cell information.
Usage examples include the library or cellcycle composition across clusters.
In this tab, users can visualise the gene expression patterns of
multiple genes grouped by categorical cell information (e.g. library / cluster).
The normalised expression are averaged, log-transformed and then plotted.