Genomic variations are associated with gene expression levels, which are called expression quantitative trait loci (eQTL). Most eQTL may affect the total gene expression levels by regulating transcriptional activities of a specific promoter. However, the direct exploration of genomic loci associated with promoter activities using RNA-seq data has been challenging because eQTL analyses treat the total expression levels estimated by summing those of all isoforms transcribed from distinct promoters. Here we propose a new method for identifying genomic loci associated with promoter activities, called promoter usage quantitative trait loci (puQTL), using conventional RNA-seq data. By leveraging public RNA-seq datasets from the lymphoblastoid cell lines of 438 individuals from the GEUVADIS project, we obtained promoter activity estimates and mapped 2,592 puQTL at the 10% FDR level. The results of puQTL mapping enabled us to interpret the manner in which genomic variations regulate gene expression. We found that 310 puQTL genes (16.1%) were not detected by eQTL analysis, suggesting that our pipeline can identify novel variant-gene associations. Furthermore, we identified genomic loci associated with the activity of "hidden" promoters, which the standard eQTL studies have ignored. We found that most puQTL signals were concordant with at least one genome-wide association study (GWAS) signal, enabling novel interpretations of the molecular mechanisms of complex traits. Our results emphasize the importance of the re-analysis of public RNA-seq datasets to obtain novel insights into gene regulation by genomic variations and their contributions to complex traits.

UNLABELLED: Genome sequence alignments provide valuable information on many aspects of molecular biological processes. In this study, we developed a web server, GenomeCons, for manipulating multiple genome sequence alignments and their consensus sequences for high-throughput genome sequence analyses. This server facilitates the visual inspection of multiple genome sequence alignments for a set of genomic intervals at a time. This allows the user to examine how these sites are evolutionarily conserved over time for their functional importance. The server also reports consensus sequences for the input genomic intervals, which can be applied to downstream analyses such as the identification of common motifs in the regions determined by ChIP-seq experiments. AVAILABILITY AND IMPLEMENTATION: GenomeCons is freely accessible at http://bioinfo.sls.kyushu-u.ac.jp/genomecons/ CONTACT: [email protected].

SUMMARY: Mutually exclusive splicing is a strictly regulated pattern of alternative splicing. A specific group of mutually exclusive splicing events has been shown to be regulated by the formation of specific RNA secondary structures. This type of regulation has been shown to exist only in arthropods. The present study involved a detailed sequence analysis of human gene structures that undergo mutually exclusive splicing, which showed that this type of regulation may also occur in dynamin 1 in mammals. A phylogenetic analysis revealed that the dynamin 1 orthologs in invertebrates did not share the same sequence features, which suggests that the regulatory mechanism has independently evolved in the mammalian lineage. Therefore, the emergence of this elaborate mechanism for mutually exclusive splicing may be attributable to mechanistic convergence.

The identification and classification of genes and pseudogenes in duplicated regions still constitutes a challenge for standard automated genome annotation procedures. Using an integrated homology and orthology analysis independent of current gene annotation, we have identified 9,484 and 9,017 gene duplicates in human and mouse, respectively. On the basis of the integrity of their coding regions, we have classified them into functional and inactive duplicates, allowing us to define the first consistent and comprehensive collection of 1,811 human and 1,581 mouse unprocessed pseudogenes. Furthermore, of the total of 14,172 human and mouse duplicates predicted to be functional genes, as many as 420 are not included in current reference gene databases and therefore correspond to likely novel mammalian genes. Some of these correspond to partial duplicates with less than half of the length of the original source genes, yet they are conserved and syntenic among different mammalian lineages. The genes and unprocessed pseudogenes obtained here will enable further studies on the mechanisms involved in gene duplication as well as of the fate of duplicated genes.

SUMMARY: BLAST2GENE is a program that allows a detailed analysis of genomic regions containing completely or partially duplicated genes. From a BLAST (or BL2SEQ) comparison of a protein or nucleotide query sequence with any genomic region of interest, BLAST2GENE processes all high scoring pairwise alignments (HSPs) and provides the disposition of all independent copies along the genomic fragment. The results are provided in text and PostScript formats to allow an automatic and visual evaluation of the respective region. AVAILABILITY: The program is available upon request from the authors. A web server of BLAST2GENE is maintained at http://www.bork.embl.de/blast2gene

Abstract Summary: DomCut is a program to predict inter-domain linker regions solely by amino acid sequence information. The prediction is made by using linker index deduced from a data set of domain/linker segments. The linker preference profile, which is the averaged linker index along a sequence, can be visualized in the graphical interface. Availability: The web server, together with supplementary information, is available at http://www.kazusa.or.jp/tech/suyama/domcut. The distribution version of DomCut is also available upon request from the authors. Contact: [email protected] * To whom correspondence should be addressed. † Present address: Biocomputing, EMBL, Meyerhofstrasse 1, 69012 Heidelberg, Germany.

MOTIVATION: Data on the entire structures of organelle and bacterial genomes, most of which are known to be circular, have accumulated at a rapid pace. This information enables us to utilize the locations of homologous gene pairs for measuring the dissimilarity between complete genomic structures. RESULTS: A macroscopic distance is presented for comparing circular genomes from their overall structures, on the basis of the locations of two pairs of homologous genes on the compared genomes. The novel aspect of our method is that the comparison between the genomes automatically reveals a relationship based on the information on all gene locations, by incorporating the mobility of each gene, which includes not only the gene order, but also the relative location between gene pairs. The plausibility of the newly defined distances is evaluated by means of 44 mitochondrial genomes. The genome distance shows high performance for quantitatively describing the differences between the gene organizations of the genomes. AVAILABILITY: Since the programs implementing these calculations require well-arranged gene organization data, they have not been released yet. However, one of the authors will analyze circular genomes upon request. Data on the gene organizations may be submitted electronically to the address below.

Recently we have constructed a database--the Enzyme-Reaction Database--which links a chemical structure to amino acid sequences of enzymes that recognize the chemical structure as their ligand. The total number of enzymes registered in the database is 1103 with 6668 NBRF-PIR entry codes and 1756 chemical compounds. The chemical structures and chemical names for 842 compounds are registered in the Chemical-Structure Database on the MACCS system. For each enzyme, the sequences were divided into clusters, and multiply aligned in each cluster to extract a conserved sequence. A total of 158,781 five-residue-long fragments were constructed from 433 conserved sequences and compared among different clusters of different enzymes. One of these motifs shared by different enzymes was S-G-G-L-D. The motif was conserved in both argininosuccinate synthase (EC 6.3.4.5) and asparagine synthase (glutamine-hydrolysing) (EC 6.3.5.4). This result showed that the database was useful for the analysis of the relationship between chemical structures and amino acid sequence motifs.