Combined serial analysis of gene expression and transcription factor binding site prediction identifies novel-candidate-target genes of Nr2e1 in neocortex development.

BACKGROUND: Nr2e1 (nuclear receptor subfamily 2, group e, member 1) encodes a transcription factor important in neocortex development. Previous work has shown that nuclear receptors can have hundreds of target genes, and bind more than 300 co-interacting proteins. However, recognition of the critical role of Nr2e1 in neural stem cells and neocortex development is relatively recent, thus the molecular mechanisms involved for this nuclear receptor are only beginning to be understood. Serial analysis of gene expression (SAGE), has given researchers both qualitative and quantitative information pertaining to biological processes. Thus, in this work, six LongSAGE mouse libraries were generated from laser microdissected tissue samples of dorsal VZ/SVZ (ventricular zone and subventricular zone) from the telencephalon of wild-type (Wt) and Nr2e1-null embryos at the critical development ages E13.5, E15.5, and E17.5. We then used a novel approach, implementing multiple computational methods followed by biological validation to further our understanding of Nr2e1 in neocortex development. RESULTS: In this work, we have generated a list of 1279 genes that are differentially expressed in response to altered Nr2e1 expression during in vivo neocortex development. We have refined this list to 64 candidate direct-targets of NR2E1. Our data suggested distinct roles for Nr2e1 during different neocortex developmental stages. Most importantly, our results suggest a possible novel pathway by which Nr2e1 regulates neurogenesis, which includes Lhx2 as one of the candidate direct-target genes, and SOX9 as a co-interactor. CONCLUSIONS: In conclusion, we have provided new candidate interacting partners and numerous well-developed testable hypotheses for understanding the pathways by which Nr2e1 functions to regulate neocortex development.

Identification of a set of genes showing regionally enriched expression in the mouse brain.

BACKGROUND: The Pleiades Promoter Project aims to improve gene therapy by designing human mini-promoters (< 4 kb) that drive gene expression in specific brain regions or cell-types of therapeutic interest. Our goal was to first identify genes displaying regionally enriched expression in the mouse brain so that promoters designed from orthologous human genes can then be tested to drive reporter expression in a similar pattern in the mouse brain. RESULTS: We have utilized LongSAGE to identify regionally enriched transcripts in the adult mouse brain. As supplemental strategies, we also performed a meta-analysis of published literature and inspected the Allen Brain Atlas in situ hybridization data. From a set of approximately 30,000 mouse genes, 237 were identified as showing specific or enriched expression in 30 target regions of the mouse brain. GO term over-representation among these genes revealed co-involvement in various aspects of central nervous system development and physiology. CONCLUSION: Using a multi-faceted expression validation approach, we have identified mouse genes whose human orthologs are good candidates for design of mini-promoters. These mouse genes represent molecular markers in several discrete brain regions/cell-types, which could potentially provide a mechanistic explanation of unique functions performed by each region. This set of markers may also serve as a resource for further studies of gene regulatory elements influencing brain expression.

SAGE2Splice: unmapped SAGE tags reveal novel splice junctions.

Serial analysis of gene expression (SAGE) not only is a method for profiling the global expression of genes, but also offers the opportunity for the discovery of novel transcripts. SAGE tags are mapped to known transcripts to determine the gene of origin. Tags that map neither to a known transcript nor to the genome were hypothesized to span a splice junction, for which the exon combination or exon(s) are unknown. To test this hypothesis, we have developed an algorithm, SAGE2Splice, to efficiently map SAGE tags to potential splice junctions in a genome. The algorithm consists of three search levels. A scoring scheme was designed based on position weight matrices to assess the quality of candidates. Using optimized parameters for SAGE2Splice analysis and two sets of SAGE data, candidate junctions were discovered for 5%-6% of unmapped tags. Candidates were classified into three categories, reflecting the previous annotations of the putative splice junctions. Analysis of predicted tags extracted from EST sequences demonstrated that candidate junctions having the splice junction located closer to the center of the tags are more reliable. Nine of these 12 candidates were validated by RT-PCR and sequencing, and among these, four revealed previously uncharacterized exons. Thus, SAGE2Splice provides a new functionality for the identification of novel transcripts and exons. SAGE2Splice is available online at http://www.cisreg.ca.

A mouse atlas of gene expression: large-scale digital gene-expression profiles from precisely defined developing C57BL/6J mouse tissues and cells.

We analyzed 8.55 million LongSAGE tags generated from 72 libraries. Each LongSAGE library was prepared from a different mouse tissue. Analysis of the data revealed extensive overlap with existing gene data sets and evidence for the existence of approximately 24,000 previously undescribed genomic loci. The visual cortex, pancreas, mammary gland, preimplantation embryo, and placenta contain the largest number of differentially expressed transcripts, 25% of which are previously undescribed loci.