Behavior training reverses asymmetry in hippocampal transcriptome of the cav3.2 knockout mice.

Homozygous Cav3.2 knockout mice, which are defective in the pore-forming subunit of a low voltage activated T-type calcium channel, have been documented to show impaired maintenance of late-phase long-term potentiation (L-LTP) and defective retrieval of context-associated fear memory. To investigate the role of Cav3.2 in global gene expression, we performed a microarray transcriptome study on the hippocampi of the Cav3.2-/- mice and their wild-type littermates, either naïve (untrained) or trace fear conditioned. We found a significant left-right asymmetric effect on the hippocampal transcriptome caused by the Cav3.2 knockout. Between the naive Cav3.2-/- and the naive wild-type mice, 3522 differentially expressed genes (DEGs) were found in the left hippocampus, but only 4 DEGs were found in the right hippocampus. Remarkably, the effect of Cav3.2 knockout was partially reversed by trace fear conditioning. The number of DEGs in the left hippocampus was reduced to 6 in the Cav3.2 knockout mice after trace fear conditioning, compared with the wild-type naïve mice. To our knowledge, these results demonstrate for the first time the asymmetric effects of the Cav3.2 and its partial reversal by behavior training on the hippocampal transcriptome.

Optimal word sizes for dissimilarity measures and estimation of the degree of dissimilarity between DNA sequences.

MOTIVATION: Several measures of DNA sequence dissimilarity have been developed. The purpose of this paper is 3-fold. Firstly, we compare the performance of several word-based or alignment-based methods. Secondly, we give a general guideline for choosing the window size and determining the optimal word sizes for several word-based measures at different window sizes. Thirdly, we use a large-scale simulation method to simulate data from the distribution of SK-LD (symmetric Kullback-Leibler discrepancy). These simulated data can be used to estimate the degree of dissimilarity beta between any pair of DNA sequences. RESULTS: Our study shows (1) for whole sequence similiarity/dissimilarity identification the window size taken should be as large as possible, but probably not >3000, as restricted by CPU time in practice, (2) for each measure the optimal word size increases with window size, (3) when the optimal word size is used, SK-LD performance is superior in both simulation and real data analysis, (4) the estimate beta of beta based on SK-LD can be used to filter out quickly a large number of dissimilar sequences and speed alignment-based database search for similar sequences and (5) beta is also applicable in local similarity comparison situations. For example, it can help in selecting oligo probes with high specificity and, therefore, has potential in probe design for microarrays. AVAILABILITY: The algorithm SK-LD, estimate beta and simulation software are implemented in MATLAB code, and are available at http://www.stat.ncku.edu.tw/tjwu