Structural Classification of Proteins-extended (SCOPe, http://scop.berkeley.edu) is a database of protein structural relationships that extends the SCOP database. SCOP is a manually curated ordering ...of domains from the majority of proteins of known structure in a hierarchy according to structural and evolutionary relationships. Development of the SCOP 1.x series concluded with SCOP 1.75. The ASTRAL compendium provides several databases and tools to aid in the analysis of the protein structures classified in SCOP, particularly through the use of their sequences. SCOPe extends version 1.75 of the SCOP database, using automated curation methods to classify many structures released since SCOP 1.75. We have rigorously benchmarked our automated methods to ensure that they are as accurate as manual curation, though there are many proteins to which our methods cannot be applied. SCOPe is also partially manually curated to correct some errors in SCOP. SCOPe aims to be backward compatible with SCOP, providing the same parseable files and a history of changes between all stable SCOP and SCOPe releases. SCOPe also incorporates and updates the ASTRAL database. The latest release of SCOPe, 2.03, contains 59 514 Protein Data Bank (PDB) entries, increasing the number of structures classified in SCOP by 55% and including more than 65% of the protein structures in the PDB.
Abstract
The SCOPe (Structural Classification of Proteins—extended, https://scop.berkeley.edu) database hierarchically classifies domains from the majority of proteins of known structure according to ...their structural and evolutionary relationships. SCOPe also incorporates and updates the ASTRAL compendium, which provides multiple databases and tools to aid in the analysis of the sequences and structures of proteins classified in SCOPe. Protein structures are classified using a combination of manual curation and highly precise automated methods. In the current release of SCOPe, 2.07, we have focused our manual curation efforts on larger protein structures, including the spliceosome, proteasome and RNA polymerase I, as well as many other Pfam families that had not previously been classified. Domains from these large protein complexes are distinctive in several ways: novel non-globular folds are more common, and domains from previously observed protein families often have N- or C-terminal extensions that were disordered or not present in previous structures. The current monthly release update, SCOPe 2.07–2018-10–18, classifies 90 992 PDB entries (about two thirds of PDB entries).
Abstract
The Structural Classification of Proteins—extended (SCOPe, https://scop.berkeley.edu) knowledgebase aims to provide an accurate, detailed, and comprehensive description of the structural and ...evolutionary relationships amongst the majority of proteins of known structure, along with resources for analyzing the protein structures and their sequences. Structures from the PDB are divided into domains and classified using a combination of manual curation and highly precise automated methods. In the current release of SCOPe, 2.08, we have developed search and display tools for analysis of genetic variants we mapped to structures classified in SCOPe. In order to improve the utility of SCOPe to automated methods such as deep learning classifiers that rely on multiple alignment of sequences of homologous proteins, we have introduced new machine-parseable annotations that indicate aberrant structures as well as domains that are distinguished by a smaller repeat unit. We also classified structures from 74 of the largest Pfam families not previously classified in SCOPe, and we improved our algorithm to remove N- and C-terminal cloning, expression and purification sequences from SCOPe domains. SCOPe 2.08-stable classifies 106 976 PDB entries (about 60% of PDB entries).
Generation of cDNA using random hexamer priming induces biases in the nucleotide composition at the beginning of transcriptome sequencing reads from the Illumina Genome Analyzer. The bias is ...independent of organism and laboratory and impacts the uniformity of the reads along the transcriptome. We provide a read count reweighting scheme, based on the nucleotide frequencies of the reads, that mitigates the impact of the bias.
Ultraconserved elements, unusually long regions of perfect sequence identity, are found in genes encoding numerous RNA-binding proteins including arginine-serine rich (SR) splicing factors. ...Expression of these genes is regulated via alternative splicing of the ultraconserved regions to yield mRNAs that are degraded by nonsense-mediated mRNA decay (NMD), a process termed unproductive splicing (Lareau et al. 2007; Ni et al. 2007). As all human SR genes are affected by alternative splicing and NMD, one might expect this regulation to have originated in an early SR gene and persisted as duplications expanded the SR family. But in fact, unproductive splicing of most human SR genes arose independently (Lareau et al. 2007). This paradox led us to investigate the origin and proliferation of unproductive splicing in SR genes. We demonstrate that unproductive splicing of the splicing factor SRSF5 (SRp40) is conserved among all animals and even observed in fungi; this is a rare example of alternative splicing conserved between kingdoms, yet its effect is to trigger mRNA degradation. As the gene duplicated, the ancient unproductive splicing was lost in paralogs, and distinct unproductive splicing evolved rapidly and repeatedly to take its place. SR genes have consistently employed unproductive splicing, and while it is exceptionally conserved in some of these genes, turnover in specific events among paralogs shows flexible means to the same regulatory end.
SCOPe (Structural Classification of Proteins—extended, http://scop.berkeley.edu) is a database of relationships between protein structures that extends the Structural Classification of Proteins ...(SCOP) database. SCOP is an expert-curated ordering of domains from the majority of proteins of known structure in a hierarchy according to structural and evolutionary relationships. SCOPe classifies the majority of protein structures released since SCOP development concluded in 2009, using a combination of manual curation and highly precise automated tools, aiming to have the same accuracy as fully hand-curated SCOP releases. SCOPe also incorporates and updates the ASTRAL compendium, which provides several databases and tools to aid in the analysis of the sequences and structures of proteins classified in SCOPe. SCOPe continues high-quality manual classification of new superfamilies, a key feature of SCOP. Artifacts such as expression tags are now separated into their own class, in order to distinguish them from the homology-based annotations in the remainder of the SCOPe hierarchy. SCOPe 2.06 contains 77,439 Protein Data Bank entries, double the 38,221 structures classified in SCOP.
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•SCOPe is a backward-compatible extension of the SCOP (version 1) database.•SCOPe 2.06 includes manually curated structures from 126 Pfam families not in SCOP.•SCOPe 2.06 separates cloning artifacts from the rest of the protein structure.•SCOPe now contains double the number of structures as SCOP.
Microbial community profiling using 16S rRNA gene sequences requires accurate taxonomy assignments. 'Universal' primers target conserved sequences and amplify sequences from many taxa, but they ...provide variable coverage of different environments, and regions of the rRNA gene differ in taxonomic informativeness--especially when high-throughput short-read sequencing technologies (for example, 454 and Illumina) are used. We introduce a new evaluation procedure that provides an improved measure of expected taxonomic precision when classifying environmental sequence reads from a given primer. Applying this measure to thousands of combinations of primers and read lengths, simulating single-ended and paired-end sequencing, reveals that these choices greatly affect taxonomic informativeness. The most informative sequence region may differ by environment, partly due to variable coverage of different environments in reference databases. Using our Rtax method of classifying paired-end reads, we found that paired-end sequencing provides substantial benefit in some environments including human gut, but not in others. Optimal primer choice for short reads totaling 96 nt provides 82-100% of the confident genus classifications available from longer reads.
Interpretation of genomic variation plays an essential role in the analysis of cancer and monogenic disease, and increasingly also in complex trait disease, with applications ranging from basic ...research to clinical decisions. Many computational impact prediction methods have been developed, yet the field lacks a clear consensus on their appropriate use and interpretation. The Critical Assessment of Genome Interpretation (CAGI, /'kā‐jē/) is a community experiment to objectively assess computational methods for predicting the phenotypic impacts of genomic variation. CAGI participants are provided genetic variants and make blind predictions of resulting phenotype. Independent assessors evaluate the predictions by comparing with experimental and clinical data.
CAGI has completed five editions with the goals of establishing the state of art in genome interpretation and of encouraging new methodological developments. This special issue (https://onlinelibrary.wiley.com/toc/10981004/2019/40/9) comprises reports from CAGI, focusing on the fifth edition that culminated in a conference that took place 5 to 7 July 2018. CAGI5 was comprised of 14 challenges and engaged hundreds of participants from a dozen countries. This edition had a notable increase in splicing and expression regulatory variant challenges, while also continuing challenges on clinical genomics, as well as complex disease datasets and missense variants in diseases ranging from cancer to Pompe disease to schizophrenia. Full information about CAGI is at https://genomeinterpretation.org.
Recommendations from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) for interpreting sequence variants specify the use of computational ...predictors as “supporting” level of evidence for pathogenicity or benignity using criteria PP3 and BP4, respectively. However, score intervals defined by tool developers, and ACMG/AMP recommendations that require the consensus of multiple predictors, lack quantitative support. Previously, we described a probabilistic framework that quantified the strengths of evidence (supporting, moderate, strong, very strong) within ACMG/AMP recommendations. We have extended this framework to computational predictors and introduce a new standard that converts a tool’s scores to PP3 and BP4 evidence strengths. Our approach is based on estimating the local positive predictive value and can calibrate any computational tool or other continuous-scale evidence on any variant type. We estimate thresholds (score intervals) corresponding to each strength of evidence for pathogenicity and benignity for thirteen missense variant interpretation tools, using carefully assembled independent data sets. Most tools achieved supporting evidence level for both pathogenic and benign classification using newly established thresholds. Multiple tools reached score thresholds justifying moderate and several reached strong evidence levels. One tool reached very strong evidence level for benign classification on some variants. Based on these findings, we provide recommendations for evidence-based revisions of the PP3 and BP4 ACMG/AMP criteria using individual tools and future assessment of computational methods for clinical interpretation.
We developed an approach to calibrate computational predictors to the American College of Medical Genetics and Genomics and Association for Molecular Pathology guidelines for clinical variant classification. We observed that predictors can provide much stronger evidence for variant pathogenicity/benignity than previously thought and propose updated recommendations for their clinical use.
Public health newborn screening (NBS) programs provide population-scale ascertainment of rare, treatable conditions that require urgent intervention. Tandem mass spectrometry (MS/MS) is currently ...used to screen newborns for a panel of rare inborn errors of metabolism (IEMs)
. The NBSeq project evaluated whole-exome sequencing (WES) as an innovative methodology for NBS. We obtained archived residual dried blood spots and data for nearly all IEM cases from the 4.5 million infants born in California between mid-2005 and 2013 and from some infants who screened positive by MS/MS, but were unaffected upon follow-up testing. WES had an overall sensitivity of 88% and specificity of 98.4%, compared to 99.0% and 99.8%, respectively for MS/MS, although effectiveness varied among individual IEMs. Thus, WES alone was insufficiently sensitive or specific to be a primary screen for most NBS IEMs. However, as a secondary test for infants with abnormal MS/MS screens, WES could reduce false-positive results, facilitate timely case resolution and in some instances even suggest more appropriate or specific diagnosis than that initially obtained. This study represents the largest, to date, sequencing effort of an entire population of IEM-affected cases, allowing unbiased assessment of current capabilities of WES as a tool for population screening.
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