SynGAP isoforms exert opposing effects on synaptic strength.

Alternative promoter usage and alternative splicing enable diversification of the transcriptome. Here we demonstrate that the function of Synaptic GTPase-Activating Protein (SynGAP), a key synaptic protein, is determined by the combination of its amino-terminal sequence with its carboxy-terminal sequence. 5' rapid amplification of cDNA ends and primer extension show that different N-terminal protein sequences arise through alternative promoter usage that are regulated by synaptic activity and postnatal age. Heterogeneity in C-terminal protein sequence arises through alternative splicing. Overexpression of SynGAP α1 versus α2 C-termini-containing proteins in hippocampal neurons has opposing effects on synaptic strength, decreasing and increasing miniature excitatory synaptic currents amplitude/frequency, respectively. The magnitude of this C-terminal-dependent effect is modulated by the N-terminal peptide sequence. This is the first demonstration that activity-dependent alternative promoter usage can change the function of a synaptic protein at excitatory synapses. Furthermore, the direction and degree of synaptic modulation exerted by different protein isoforms from a single gene locus is dependent on the combination of differential promoter usage and alternative splicing.

Fixed-lag blind equalization and sequence estimation in digital communications systems using sequential importance sampling

We present methods for fixed-lag smoothing using Sequential Importance sampling (SIS) on a discrete non-linear, non-Gaussian state space system with unknown parameters. Our particular application is in the field of digital communication systems. Each input data point is taken from a finite set of symbols. We represent transmission media as a fixed filter with a finite impulse response (FIR), hence a discrete state-space system is formed. Conventional Markov chain Monte Carlo (MCMC) techniques such as the Gibbs sampler are unsuitable for this task because they can only perform processing on a batch of data. Data arrives sequentially, so it would seem sensible to process it in this way. In addition, many communication systems are interactive, so there is a maximum level of latency that can be tolerated before a symbol is decoded. We will demonstrate this method by simulation and compare its performance to existing techniques.