Divergence of RNA localization between rat and mouse neurons reveals the potential for rapid brain evolution.

BACKGROUND: Neurons display a highly polarized architecture. Their ability to modify their features under intracellular and extracellular stimuli, known as synaptic plasticity, is a key component of the neurochemical basis of learning and memory. A key feature of synaptic plasticity involves the delivery of mRNAs to distinct sub-cellular domains where they are locally translated. Regulatory coordination of these spatio-temporal events is critical for synaptogenesis and synaptic plasticity as defects in these processes can lead to neurological diseases. In this work, using microdissected dendrites from primary cultures of hippocampal neurons of two mouse strains (C57BL/6 and Balb/c) and one rat strain (Sprague-Dawley), we investigate via microarrays, subcellular localization of mRNAs in dendrites of neurons to assay the evolutionary differences in subcellular dendritic transcripts localization. RESULTS: Our microarray analysis highlighted significantly greater evolutionary diversification of RNA localization in the dendritic transcriptomes (81% gene identity difference among the top 5% highly expressed genes) compared to the transcriptomes of 11 different central nervous system (CNS) and non-CNS tissues (average of 44% gene identity difference among the top 5% highly expressed genes). Differentially localized genes include many genes involved in CNS function. CONCLUSIONS: Species differences in sub-cellular localization may reflect non-functional neutral drift. However, the functional categories of mRNA showing differential localization suggest that at least part of the divergence may reflect activity-dependent functional differences of neurons, mediated by species-specific RNA subcellular localization mechanisms.

Evolutionary coupling in the K(V)1.2-ß2 complex.

K(V)1.2 is a potassium channel protein whose electrophysiological properties, including an oxygen sensing response, are modulated by auxiliary beta subunits. The beta subunits are homologous to oxidoreductases, supporting a hypothesis that the coupling of the two subunits helps connect the redox state of the cell to the electrical activity of the membrane. However the exact mechanism of the coupling has not been discovered to-date. We apply evolutionary correlation analysis to infer previously unknown components of the interaction network regulating the response to hypoxia of the K(V)1.2/ß2 complex. Briefly, evolutionary correlation analysis involves finding correlated amino acid substitutions in functionally equivalent proteins (for both subunits) across a range of species. The method thus depends on a reliable method of inferring functionally equivalent (orthologous) proteins in different species, which method we describe in a paper recently published in PLoS ONE. One key finding is the characterization of a network of motif interactions between the α and the ß subunits. By significance testing, we show that the likelihood of the correlations shown in the K(V)1.2-ß two interaction motifs arising by chance is less than 0.0003, which shows that the correlations are statistically highly significant. We therefore believe that the correlations are likely to be biologically relevant. Other major findings are correlations between specific motifs in the K(V)1.2-ß2 complex and motifs in other proteins such as RACK1 and Eif36sip, which in turn are connected to the hypoxia response. Our paper combines this correlation with the literature evidence on potassium channel inactivation and hypoxia response to identify specific motifs to serve as experimental targets for studies focused on this response. This work aims to add to our general understanding of two major issues in ion channel science: 1) how multi-protein complexes including ion channels function in coordinated fashion, and 2) how ion channels mediate the conversation between the intracellular and extracellular environments. We also aim to apply to ion channel science the principle that domain-domain interactions in proteins can be inferred from correlation of amino-acid substitutions in sets of functionally equivalent proteins.

Functional equivalency inferred from "authoritative sources" in networks of homologous proteins.

A one-on-one mapping of protein functionality across different species is a critical component of comparative analysis. This paper presents a heuristic algorithm for discovering the Most Likely Functional Counterparts (MoLFunCs) of a protein, based on simple concepts from network theory. A key feature of our algorithm is utilization of the user's knowledge to assign high confidence to selected functional identification. We show use of the algorithm to retrieve functional equivalents for 7 membrane proteins, from an exploration of almost 40 genomes form multiple online resources. We verify the functional equivalency of our dataset through a series of tests that include sequence, structure and function comparisons. Comparison is made to the OMA methodology, which also identifies one-on-one mapping between proteins from different species. Based on that comparison, we believe that incorporation of user's knowledge as a key aspect of the technique adds value to purely statistical formal methods.

A 1463 gene cattle-human comparative map with anchor points defined by human genome sequence coordinates.

A second-generation 5000 rad radiation hybrid (RH) map of the cattle genome was constructed primarily using cattle ESTs that were targeted to gaps in the existing cattle-human comparative map, as well as to sparsely populated map intervals. A total of 870 targeted markers were added, bringing the number of markers mapped on the RH(5000) panel to 1913. Of these, 1463 have significant BLASTN hits (E < e(-5)) against the human genome sequence. A cattle-human comparative map was created using human genome sequence coordinates of the paired orthologs. One-hundred and ninety-five conserved segments (defined by two or more genes) were identified between the cattle and human genomes, of which 31 are newly discovered and 34 were extended singletons on the first-generation map. The new map represents an improvement of 20% genome-wide comparative coverage compared with the first-generation map. Analysis of gene content within human genome regions where there are gaps in the comparative map revealed gaps with both significantly greater and significantly lower gene content. The new, more detailed cattle-human comparative map provides an improved resource for the analysis of mammalian chromosome evolution, the identification of candidate genes for economically important traits, and for proper alignment of sequence contigs on cattle chromosomes.

Multi-species comparative mapping in silico using the COMPASS strategy.

MOTIVATION: The completion of human and mouse genome sequences provides a valuable resource for decoding other mammalian genomes. The comparative mapping by annotation and sequence similarity (COMPASS) strategy takes advantage of the resource and has been used in several genome-mapping projects. It uses existing comparative genome maps based on conserved regions to predict map locations of a sequence. An automated multiple-species COMPASS tool can facilitate in the genome sequencing effort and comparative genomics study of other mammalian species. RESULTS: The prerequisite of COMPASS is a comparative map table between the reference genome and the predicting genome. We have built and collected comparative maps among five species including human, cattle, pig, mouse and rat. Cattle-human and pig-human comparative maps were built based on the positions of orthologous markers and the conserved synteny groups between human and cattle and human and pig genomes, respectively. Mouse-human and rat-human comparative maps were based on the conserved sequence segments between the two genomes. With a match to human genome sequences, the approximate location of a query sequence can be predicted in cattle, pig, mouse and rat genomes based on the position of the match relatively to the orthologous markers or the conserved segments. AVAILABILITY: The COMPASS-tool and databases are available at http://titan.biotec.uiuc.edu/COMPASS/