Assembling genes from predicted exons in linear time with dynamic programming

In a number of programs for gene structure prediction in higher eukaryotic genomic sequences, exon prediction is decoupled from gene assembly: a large pool of candidate exons is predicted and scored from features located in the query DNA sequence, and candidate genes are assembled from such a pool as sequences of nonoverlapping frame-compatible exons. Genes are scored as a function of the scores of the assembled exons, and the highest scoring candidate gene is assumed to be the most likely gene encoded by the query DNA sequence. Considering additive gene scoring functions, currently available algorithms to determine such a highest scoring candidate gene run in time proportional to the square of the number of predicted exons. Here, we present an algorithm whose running time grows only linearly with the size of the set of predicted exons. Polynomial algorithms rely on the fact that, while scanning the set of predicted exons, the highest scoring gene ending in a given exon can be obtained by appending the exon to the highest scoring among the highest scoring genes ending at each compatible preceding exon. The algorithm here relies on the simple fact that such highest scoring gene can be stored and updated. This requires scanning the set of predicted exons simultaneously by increasing acceptor and donor position. On the other hand, the algorithm described here does not assume an underlying gene structure model. Indeed, the definition of valid gene structures is externally defined in the so-called Gene Model. The Gene Model specifies simply which gene features are allowed immediately upstream which other gene features in valid gene structures. This allows for great flexibility in formulating the gene identification problem. In particular it allows for multiple-gene two-strand predictions and for considering gene features other than coding exons (such as promoter elements) in valid gene structures.

Multi-receptor binding profile of clozapine and olanzapine: a structural study based on the new beta (2) adrenergic receptor template

Schizophrenia is a devastating mental disorder that has a largeimpact on the quality of life for those who are afflicted and isvery costly for families and society.[1] Although the etiology ofschizophrenia is still unknown and no cure has yet beenfound, it is treatable, and pharmacological therapy often producessatisfactory results. Among the various antipsychoticdrugs in use, clozapine is widely recognized as one ofthemost clinically effective agents, even if it elicits significant sideeffects such as metabolic disorders and agranulocytosis. Clozapineand the closely related compound olanzapine are goodexamples ofdrug s with a complex multi-receptor profile ;[2]they have affinities toward serotonin, dopamine, a adrenergic,muscarinic, and histamine receptors, among others.

Comparative gene finding in chicken indicates that we are closing in on the set of multi-exonic widely-expressed human genes

The recent availability of the chicken genome sequence poses the question of whether there are human protein-coding genes conserved in chicken that are currently not included in the human gene catalog. Here, we show, using comparative gene finding followed by experimental verification of exon pairs by RT–PCR, that the addition to the multi-exonic subset of this catalog could be as little as 0.2%, suggesting that we may be closing in on the human gene set. Our protocol, however, has two shortcomings: (i) the bioinformatic screening of the predicted genes, applied to filter out false positives, cannot handle intronless genes; and (ii) the experimental verification could fail to identify expression at a specific developmental time. This highlights the importance of developing methods that could provide a reliable estimate of the number of these two types of genes.

Analysis of the multi-copy gene family FAM90A as a copy number variant in different ethnic backgrounds

Copy number variants contribute extensively to inter-individual genomic differences, but little is known about their inter-population variability and diversity. In a previous study (Bosch et al., 2007; 16:2572-2582), we reported that the primate-specific gene family FAM90A, which accounts for as many as 25 members in the human reference assembly, has expanded the number of FAM90A clusters across the hominoid lineage. Here we examined the copy number variability of FAM90A genes in 260 HapMap samples of European, African, and Asian ancestry, and showed significant inter-population differences (p<0.0001). Based on the recent study of Stranger et al. (2007; 315:848-853), we also explored the correlation between copy number variability and expression levels of the FAM90A gene family. Despite the high genomic variability, we found a low correlation between FAM90A copy number and expression levels, which could be due to the action of independent trans-acting factors. Our results show that FAM90A is highly variable in copy number between individuals and between populations. However, this variability has little impact on gene expression levels, thus highlighting the importance of genomic variability for genes located in regions containing segmental duplications.

Capacity-achieving input covariance for single-user multi-antenna channels

We characterize the capacity-achieving input covariance for multi-antenna channels known instantaneously at the receiver and in distribution at the transmitter. Our characterization, valid for arbitrary numbers of antennas, encompasses both the eigenvectors and the eigenvalues. The eigenvectors are found for zero-mean channels with arbitrary fading profiles and a wide range of correlation and keyhole structures. For the eigenvalues, in turn, we present necessary and sufficient conditions as well as an iterative algorithm that exhibits remarkable properties: universal applicability, robustness and rapid convergence. In addition, we identify channel structures for which an isotropic input achieves capacity.