Molecular characterization of foveal versus peripheral human retina by single-cell RNA sequencing.

The human retina is a complex tissue responsible for detecting photons of light and converting information from these photons into the neurochemical signals interpreted as vision. Such visual signaling not only requires sophisticated interactions between multiple classes of neurons, but also spatially-dependent molecular specialization of individual cell types. In this study, we performed single-cell RNA sequencing on neural retina isolated from both the fovea and peripheral retina in three human donors. We recovered a total of 8,217 cells, with 3,578 cells originating from the fovea and 4,639 cells originating from the periphery. Expression profiles for all major retinal cell types were compiled, and differential expression analysis was performed between cells of foveal versus peripheral origin. Globally, mRNA for the serum iron binding protein transferrin (TF), which has been associated with age-related macular degeneration pathogenesis, was enriched in peripheral samples. Cone photoreceptor cells were of particular interest and formed two predominant clusters based on gene expression. One cone cluster had 96% of cells originating from foveal samples, while the second cone cluster consisted exclusively of peripherally isolated cells. A total of 148 genes were differentially expressed between cones from the fovea versus periphery. Interestingly, peripheral cones were enriched for the gene encoding Beta-Carotene Oxygenase 2 (BCO2). A relative deficiency of this enzyme may account for the accumulation of carotenoids responsible for yellow pigment deposition within the macula. Overall, this data set provides rich expression profiles of the major human retinal cell types and highlights transcriptomic features that distinguish foveal and peripheral cells.

Pooled library tissue tags for EST-based gene discovery.

MOTIVATION: In gene discovery projects based on EST sequencing, effective post-sequencing identification methods are important in determining tissue sources of ESTs within pooled cDNA libraries. In the past, such identification efforts have been characterized by higher than necessary failure rates due to the presence of errors within the subsequence containing the oligo tag intended to define the tissue source for each EST. RESULTS: A large-scale EST-based gene discovery program at The University of Iowa has led to the creation of a unique software method named UITagCreator usable in the creation of large sets of synthetic tissue identification tags. The identification tags provide error detection and correction capability and, in conjunction with automated annotation software, result in a substantial improvement in the accurate identification of the tissue source in the presence of sequencing and base-calling errors. These identification rates are favorable, relative to past paradigms. AVAILABILITY: The UITagCreator source code and installation instructions, along with detection software usable in concert with created tag sets, is freely available at http://genome.uiowa.edu/pubsoft/software.html CONTACT: tomc@eng.uiowa.edu

Automated construction of high-density comparative maps between rat, human, and mouse.

Animal models have been used primarily as surrogates for humans, having similar disease-based phenotypes. Genomic organization also tends to be conserved between species, leading to the generation of comparative genome maps. The emergence of radiation hybrid (RH) maps, coupled with the large numbers of available Expressed Sequence Tags (ESTs), has revolutionized the way comparative maps can be built. We used publicly available rat, mouse, and human data to identify genes and ESTs with interspecies sequence identity (homology), identified their UniGene relationships, and incorporated their RH map positions to build integrated comparative maps with >2100 homologous UniGenes mapped in more than one species (approximately 6% of all mammalian genes). The generation of these maps is iterative and labor intensive; therefore, we developed a series of computer tools (not described here) based on our algorithm that identifies anchors between species and produces printable and on-line clickable comparative maps that link to a wide variety of useful tools and databases. The maps were constructed using sequence-based comparisons, thus creating "hooks" for further sequence-based annotation of human, mouse, and rat sequences. Currently, this map enables investigators to link the physiology of the rat with the genetics of the mouse and the clinical significance of the human.

Generation of a high-density rat EST map.

We have developed a high-density EST map of the rat, consisting of >11,000 ESTs. These ESTs were placed on a radiation hybrid framework map of genetic markers spanning all 20 rat autosomes, plus the X chromosome. The framework maps have a total size of approximately 12,400 cR, giving an average correspondence of 240 kb/cR. The frameworks are all LOD 3 chromosomal maps consisting of 775 radiation-hybrid-mapped genetic markers and ESTs. To date, we have generated radiation-hybrid-mapping data for >14,000 novel ESTs identified by our Rat Gene Discovery and Mapping Project (http://ratEST.uiowa.edu), from which we have placed >11,000 on our framework maps. To minimize mapping errors, ESTs were mapped in duplicate and consensus RH vectors produced for use in the placement procedure. This EST map was then used to construct high-density comparative maps between rat and human and rat and mouse. These maps will be a useful resource for positional cloning of genes for rat models of human diseases and in the creation and verification of a tiling set of map order for the upcoming rat-genome sequencing.