Differential hippocampal gene expression is associated with climate-related natural variation in memory and the hippocampus in food-caching chickadees

There is significant and often heritable variation in cognition and its underlying neural mechanisms, yet specific genetic contributions to such variation are not well characterized. Black-capped chickadees present a good model to investigate the genetic basis of cognition because they exhibit tremendous climate-related variation in memory, hippocampal morphology and neurogenesis rates throughout the North American continent, and these cognitive traits appear to have a heritable basis. We examined the hippocampal transcriptome profiles of laboratory-reared chickadees from the two most divergent populations to test whether differential gene expression in the hippocampus is associated with population differences in spatial memory, hippocampal morphology and adult hippocampal neurogenesis rates. Using high-resolution mRNA sequencing coupled to a de novo transcriptome assembly, we generated 23 295 consensus sequences, which predicted 16 206 protein sequences with 13 982 showing high similarity to known protein sequences or conserved hypothetical proteins in other species. Of these, we identified differential expression in nearly 380 genes, with 47 genes specifically linked to neurogenesis, apoptosis, synaptic function, and learning and memory processes. Many of the other differentially expressed genes, however, may be associated with other functions. Our study presents the first avian hippocampal transcriptome, and it is the first study identifying differential gene expression associated with natural variation in cognition and the hippocampus. Our results provide additional support to the hypothesis that population differences in memory, hippocampal morphology and neurogenesis in chickadees have likely resulted from natural selection that appears to act on memory and its underlying neural mechanisms.

The genome sequence DataBase

The Genome Sequence DataBase (GSDB) is a database of publicly available nucleotide sequences and their associated biological and bibliographic information. Several notable changes have occurred in the past year: GSDB stopped accepting data submissions from researchers; ownership of data submitted to GSDB was transferred to GenBank; sequence analysis capabilities were expanded to include Smith-Waterman and Frame Search; and Sequence Viewer became available to Mac users. The content of GSDB remains up-to-date because publicly available data is acquired from the International Nucleotide Sequence Database Collaboration databases (IC) on a nightly basis. This allows GSDB to continue providing researchers with the ability to analyze, query and retrieve nucleotide sequences in the database. GSDB and its related tools are freely accessible from the URL: http://www.ncgr.org

The Genome Sequence DataBase: towards an integrated functional genomics resource

During 1998 the primary focus of the Genome Sequence DataBase (GSDB; http://www.ncgr.org/gsdb ) located at the National Center for Genome Resources (NCGR) has been to improve data quality, improve data collections, and provide new methods and tools to access and analyze data. Data quality has been improved by extensive curation of certain data fields necessary for maintaining data collections and for using certain tools. Data quality has also been increased by improvements to the suite of programs that import data from the International Nucleotide Sequence Database Collaboration (IC). The Sequence Tag Alignment and Consensus Knowledgebase (STACK), a database of human expressed gene sequences developed by the South African National Bioinformatics Institute (SANBI), became available within the last year, allowing public access to this valuable resource of expressed sequences. Data access was improved by the addition of the Sequence Viewer, a platform-independent graphical viewer for GSDB sequence data. This tool has also been integrated with other searching and data retrieval tools. A BLAST homology search service was also made available, allowing researchers to search all of the data, including the unique data, that are available from GSDB. These improvements are designed to make GSDB more accessible to users, extend the rich searching capability already present in GSDB, and to facilitate the transition to an integrated system containing many different types of biological data.