Transcriptomic variation of pharmacogenes in multiple human tissues and lymphoblastoid cell lines.

Variation in the expression level and activity of genes involved in drug disposition and action ('pharmacogenes') can affect drug response and toxicity, especially when in tissues of pharmacological importance. Previous studies have relied primarily on microarrays to understand gene expression differences, or have focused on a single tissue or small number of samples. The goal of this study was to use RNA-sequencing (RNA-seq) to determine the expression levels and alternative splicing of 389 Pharmacogenomics Research Network pharmacogenes across four tissues (liver, kidney, heart and adipose) and lymphoblastoid cell lines, which are used widely in pharmacogenomics studies. Analysis of RNA-seq data from 139 different individuals across the 5 tissues (20-45 individuals per tissue type) revealed substantial variation in both expression levels and splicing across samples and tissue types. Comparison with GTEx data yielded a consistent picture. This in-depth exploration also revealed 183 splicing events in pharmacogenes that were previously not annotated. Overall, this study serves as a rich resource for the research community to inform biomarker and drug discovery and use.

Population statistics of protein structures: lessons from structural classifications.

Structural classifications aid the interpretation of proteins by describing degrees of structural and evolutionary relatedness. They have also recently revealed strikingly skewed distributions at all levels; for example, a small number of folds are far more common than others, and just a few superfamilies are known to have diverged widely. The classifications also provide an indication of the total number of superfamilies in nature.

SCOP: a structural classification of proteins database for the investigation of sequences and structures.

To facilitate understanding of, and access to, the information available for protein structures, we have constructed the Structural Classification of Proteins (scop) database. This database provides a detailed and comprehensive description of the structural and evolutionary relationships of the proteins of known structure. It also provides for each entry links to co-ordinates, images of the structure, interactive viewers, sequence data and literature references. Two search facilities are available. The homology search permits users to enter a sequence and obtain a list of any structures to which it has significant levels of sequence similarity. The key word search finds, for a word entered by the user, matches from both the text of the scop database and the headers of Brookhaven Protein Databank structure files. The database is freely accessible on World Wide Web (WWW) with an entry point to URL http: parallel scop.mrc-lmb.cam.ac.uk magnitude of scop.

A quantitative methodology for the de novo design of proteins.

We have developed a general quantitative methodology for designing proteins de novo, which automatically produces sequences for any given plausible protein structure. The method incorporates statistical information, a theoretical description of protein structure, and motifs described in the literature. A model system embodying a portion of the quantitative methodology has been used to design many protein sequences for the phage 434 Cro and fibronectin type III domain folds, as well as several other structures. Residue sequences selected by this prototype share no significant identity with any natural protein. Nonetheless, 3-dimensional models of the designed sequences appear generally plausible. When examined using secondary structure prediction methods and profile analysis, the designed sequences generally score considerably better than the natural ones. The designed sequences are also in reasonable agreement with a sequence template. This quantitative methodology is likely to be capable of successfully designing new proteins and yielding fundamental insights about the determinants of protein structure.

Expectations from structural genomics.

Structural genomics projects aim to provide an experimental structure or a good model for every protein in all completed genomes. Most of the experimental work for these projects will be directed toward proteins whose fold cannot be readily recognized by simple sequence comparison with proteins of known structure. Based on the history of proteins classified in the SCOP structure database, we expect that only about a quarter of the early structural genomics targets will have a new fold. Among the remaining ones, about half are likely to be evolutionarily related to proteins of known structure, even though the homology could not be readily detected by sequence analysis.

Classification of multi-helical DNA-binding domains and application to predict the DBD structures of sigma factor, LysR, OmpR/PhoB, CENP-B, Rapl, and Xy1S/Ada/AraC.

We have systematically compared structures of multi-helical DNA-binding domains (DBDs) which have been determined by crystallography or NMR spectroscopy. All the known multi-helical DBDs are very similar. The core of these structures consists of two alpha-helices in the helix-turn-helix combination, associated with one or two other helices. The structures can be classified according to either additional structural compositions or the configuration of the helices. Many DBDs, whose structures are currently unknown, have sequences which resemble those of known structures, permitting outlines of the new structures to be predicted.

The transcriptional landscape of the mammalian genome.

This study describes comprehensive polling of transcription start and termination sites and analysis of previously unidentified full-length complementary DNAs derived from the mouse genome. We identify the 5' and 3' boundaries of 181,047 transcripts with extensive variation in transcripts arising from alternative promoter usage, splicing, and polyadenylation. There are 16,247 new mouse protein-coding transcripts, including 5154 encoding previously unidentified proteins. Genomic mapping of the transcriptome reveals transcriptional forests, with overlapping transcription on both strands, separated by deserts in which few transcripts are observed. The data provide a comprehensive platform for the comparative analysis of mammalian transcriptional regulation in differentiation and development.

A tour of structural genomics.

Structural genomics projects aim to provide an experimental or computational three-dimensional model structure for all of the tractable macromolecules that are encoded by complete genomes. To this end, pilot centres worldwide are now exploring the feasibility of large-scale structure determination. Their experimental structures and computational models are expected to yield insight into the molecular function and mechanism of thousands of proteins. The pervasiveness of this information is likely to change the use of structure in molecular biology and biochemistry.

Target selection for structural genomics.

Structural genomics aims to use high-throughput structure determination and computational analysis to provide three-dimensional models of every tractable protein. The process of choosing proteins for experimental structure characterization is known as target selection. In this nomenclature, the targets are regions of proteins to be studied by crystallography or NMR. Selection of the targets is principally a computational process of restricting candidate proteins to those that are tractable and of unknown structure, and prioritizing according to expected interest and accessibility.

Protein design by optimization of a sequence-structure quality function.

An automated procedure for protein design by optimization of a sequence-structure quality has been developed. The method selects a statistically optimal sequence for a particular structure, on the assumption that such a protein will adopt the desired structure. We present two optimization algorithms: one provides an exact optimization while the other uses a combinatorial technique for comparatively rapid results. Both are suitable for massively parallel computers. A prototype system was used to design sequences which should adopt the four-helix bundle conformation of myohemerythrin. These appear satisfactory to secondary structure and profile analysis. Detailed inspection reveals that the sequences are generally plausible but, as expected, lack some specific structural features. The design parameters provide some insight into the general determinants of protein structure.

A specification for defining and annotating regions of macromolecular structures.

We present a program- and machine-independent standard for annotating macromolecular structures. Data encoded by this specification may be used for communicating information about structures and for exchanging it between different computer systems. The format consists of a set of ASN.1 objects which are mechanically straightforward to parse, but are also easy for humans to create and understand. It differs from all other related standards in that it specifies how a molecule should be displayed without requiring a custom format for the coordinate data.

The PRESAGE database for structural genomics.

The PRESAGE database is a collaborative resource for structural genomics. It provides a database of proteins to which researchers add annotations indicating current experimental status, structural predictions and suggestions. The database is intended to enhance communication among structural genomics researchers and aid dissemination of their results. The PRESAGE database may be accessed at http://presage.stanford.edu/

Computational prediction of membrane-tethered transcription factors.

BACKGROUND: Sequestration of transcription factors in the membrane is emerging as an important mechanism for the regulation of gene expression. A handful of membrane-spanning transcription factors has been previously identified whose access to the nucleus is regulated by proteolytic cleavage from the membrane. To investigate the existence of other transmembrane transcription factors, we analyzed computationally all proteins in SWISS-PROT/TrEMBL for the combined presence of a DNA-binding domain and a transmembrane segment. RESULTS: Using Pfam hidden Markov models and four transmembrane-prediction programs, we identified with high confidence 76 membrane-spanning transcription factors in SWISS-PROT/TrEMBL. Analysis of the distribution of two proteins predicted by our method, MTJ1 and DMRT2, confirmed their localization to intracellular membrane compartments. Furthermore, elimination of the predicted transmembrane segment led to nuclear localization for each of these proteins. CONCLUSIONS: Our analysis uncovered a wealth of predicted membrane-spanning transcription factors that are structurally and taxonomically diverse, 56 of which lack experimental annotation. Seventy-five of the proteins are modular in structure, suggesting that a single proteolysis may be sufficient to liberate a DNA-binding domain from the membrane. This study provides grounds for investigations into the stimuli and mechanisms that release this intriguing class of transcription factors from membranes.

Assessing sequence comparison methods with reliable structurally identified distant evolutionary relationships.

Pairwise sequence comparison methods have been assessed using proteins whose relationships are known reliably from their structures and functions, as described in the SCOP database [Murzin, A. G., Brenner, S. E., Hubbard, T. & Chothia C. (1995) J. Mol. Biol. 247, 536-540]. The evaluation tested the programs BLAST [Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. (1990). J. Mol. Biol. 215, 403-410], WU-BLAST2 [Altschul, S. F. & Gish, W. (1996) Methods Enzymol. 266, 460-480], FASTA [Pearson, W. R. & Lipman, D. J. (1988) Proc. Natl. Acad. Sci. USA 85, 2444-2448], and SSEARCH [Smith, T. F. & Waterman, M. S. (1981) J. Mol. Biol. 147, 195-197] and their scoring schemes. The error rate of all algorithms is greatly reduced by using statistical scores to evaluate matches rather than percentage identity or raw scores. The E-value statistical scores of SSEARCH and FASTA are reliable: the number of false positives found in our tests agrees well with the scores reported. However, the P-values reported by BLAST and WU-BLAST2 exaggerate significance by orders of magnitude. SSEARCH, FASTA ktup = 1, and WU-BLAST2 perform best, and they are capable of detecting almost all relationships between proteins whose sequence identities are >30%. For more distantly related proteins, they do much less well; only one-half of the relationships between proteins with 20-30% identity are found. Because many homologs have low sequence similarity, most distant relationships cannot be detected by any pairwise comparison method; however, those which are identified may be used with confidence.

The ASTRAL compendium for protein structure and sequence analysis.

The ASTRAL compendium provides several databases and tools to aid in the analysis of protein structures, particularly through the use of their sequences. The SPACI scores included in the system summarize the overall characteristics of a protein structure. A structural alignments database indicates residue equivalencies in superimposed protein domain structures. The PDB sequence-map files provide a linkage between the amino acid sequence of the molecule studied (SEQRES records in a database entry) and the sequence of the atoms experimentally observed in the structure (ATOM records). These maps are combined with information in the SCOPdatabase to provide sequences of protein domains. Selected subsets of the domain database, with varying degrees of similarity measured in several different ways, are also available. ASTRALmay be accessed at http://astral.stanford.edu/