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PubMed2025

Chromosomal level genome assembly of medicinal plant Chrysosplenium macrophyllum.

Chrysosplenium macrophyllum Oliv., a perennial herb native to China, is widely used in traditional medicine for its notable therapeutic properties. However, the absence of a reference genome has constrained its full potential for research and application. This study presents the first chromosome-level de novo genome assembly of C. macrophyllum, constructed by integrating long reads from Oxford Nanopore Technologies (ONT), short reads from BGI, and Hi-C data. The final assembly spans 2.55 Gb, with a scaffold N50 of 93.38 Mb, and 83.70% of the genome has been assigned to 22 chromosomes. The mapping rate of the BGI short reads to the genome is approximately 97.94%, and BUSCO analysis reveals that 97.94% of the predicted genes are complete. A total of 62,921 protein-coding genes were predicted, with functional annotations for 93.67% of them. This chromosome-level genome assembly represents an important resource for expanding our understanding of Chrysosplenium species and supports future genomic studies and applications.

Genome, Plant↗
PubMed1993

The SBASE domain library: a collection of annotated protein segments.

SBASE is a database of annotated protein domain sequences representing various structural, functional, ligand binding and topogenic segments of proteins. The current release of SBASE contains 27,211 entries which are provided with standardized names in order to facilitate retrieval. SBASE is cross-referenced to the major protein and nucleic acid databanks as well as to the PROSITE catalog of protein sequence patterns [Bairoch, A. (1992) Nucleic Acids Res., 20, Suppl., 2013-2118]. SBASE can be used to establish domain homologies through database search using programs such as FASTA [Lipman and Pearson (1985) Science, 227, 1436-1441], FASTDB [Brutlag et al. (1990) Comp. Appl. Biosci., 6, 237-245] or BLAST3 [Altschul and Lipman (1990) Proc. Natl. Acad. Sci. USA, 87, 5509-5513], which is especially useful in the case of loosely defined domain types for which efficient consensus patterns cannot be established. The use of SBASE is illustrated on the DNA binding protein Brain-4. The database and a set of search and retrieval tools are freely available on request to the authors or by anonymous 'ftp' file transfer from < ftp.icgeb.trieste.it >.

Amino Acid Sequence↗
PubMed2005

Comparative plant genomics resources at PlantGDB.

PlantGDB (http://www.plantgdb.org/) is a database of plant molecular sequences. Expressed sequence tag (EST) sequences are assembled into contigs that represent tentative unique genes. EST contigs are functionally annotated with information derived from known protein sequences that are highly similar to the putative translation products. Tentative Gene Ontology terms are assigned to match those of the similar sequences identified. Genome survey sequences are assembled similarly. The resulting genome survey sequence contigs are matched to ESTs and conserved protein homologs to identify putative full-length open reading frame-containing genes, which are subsequently provisionally classified according to established gene family designations. For Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa), the exon-intron boundaries for gene structures are annotated by spliced alignment of ESTs and full-length cDNAs to their respective complete genome sequences. Unique genome browsers have been developed to present all available EST and cDNA evidence for current transcript models (for Arabidopsis, see the AtGDB site at http://www.plantgdb.org/AtGDB/; for rice, see the OsGDB site at http://www.plantgdb.org/OsGDB/). In addition, a number of bioinformatic tools have been integrated at PlantGDB that enable researchers to carry out sequence analyses on-site using both their own data and data residing within the database.

Computational Biology↗
PubMed2006

Phylogenetic analysis of general bacterial porins: a phylogenomic case study.

Bacterial porin proteins allow for the selective movement of hydrophilic solutes through the outer membrane of Gram-negative bacteria. The purpose of this study was to clarify the evolutionary relationships among the Type 1 general bacterial porins (GBPs), a porin protein subfamily that includes outer membrane proteins ompC and ompF among others. Specifically, we investigated the potential utility of phylogenetic analysis for refining poorly annotated or mis-annotated protein sequences in databases, and for characterizing new functionally distinct groups of porin proteins. Preliminary phylogenetic analysis of sequences obtained from GenBank indicated that many of these sequences were incompletely or even incorrectly annotated. Using a well-curated set of porins classified via comparative genomics, we applied recently developed bayesian phylogenetic methods for protein sequence analysis to determine the relationships among the Type 1 GBPs. Our analysis found that the major GBP classes (ompC, phoE, nmpC and ompN) formed strongly supported monophyletic groups, with the exception of ompF, which split into two distinct clades. The relationships of the GBP groups to one another had less statistical support, except for the relationships of ompC and ompN sequences, which were strongly supported as sister groups. A phylogenetic analysis comparing the relationships of the GenBank GBP sequences to the correctly annotated set of GBPs identified a large number of previously unclassified and mis-annotated GBPs. Given these promising results, we developed a tree-parsing algorithm for automated phylogenetic annotation and tested it with GenBank sequences. Our algorithm was able to automatically classify 30 unidentified and 15 mis-annotated GBPs out of 78 sequences. Altogether, our results support the potential for phylogenomics to increase the accuracy of sequence annotations.

Algorithms↗
PubMed2025

RNAi screening of uncharacterized genes identifies promising druggable targets in Schistosoma japonicum.

Schistosomiasis affects more than 250 million people worldwide and is one of the neglected tropical diseases. Currently, the treatment of schistosomiasis relies on a single drug-praziquantel-which has led to increasing pressure from drug resistance. Therefore, there is an urgent need to find new treatments. The development of genome sequencing has provided valuable information for understanding the biology of schistosomes. In the genome of Schistosoma japonicum, approximately 11% of the protein-coding sequences are uncharacterized genes (UGs) annotated as "hypothetical protein" or "protein of unknown function." These poorly understood genes have been unjustifiably neglected, although some may be essential for the survival of the parasites and serve as potential drug targets. In this study, we systematically mined the highly expressed UGs in both genders of this parasite throughout key developmental stages in their mammalian host, using our previously published S. japonicum genome and RNA-seq data. By employing in vitro RNA interference (RNAi), we screened 126 UGs that lack homologs in Homo sapiens and identified 8 that are essential for the parasite vitality. We further investigated two UGs, Sjc_0002003 and Sjc_0009272, which resulted in the most severe phenotypes. Fluorescence in situ hybridization demonstrated that both genes were expressed throughout the body without sex bias. Silencing either Sjc_0002003 or Sjc_0009272 reduced the cell proliferation in the body. Furthermore, in vivo RNAi indicated both genes are required for the growth and survival of the parasites in the mammalian host. For Sjc_0002003, we further characterize the underlying molecular cause of the observed phenotype. Through RNA-seq analysis and functional studies, we revealed that silencing Sjc_0002003 reduces the expression of a series of intestinal genes, including Sjc_0007312 (hypothetical protein), Sjc_0008276 (vha-17), Sjc_0002942 (PLA2G15), and Sjc_0003646 (SJCHGC09134 protein), leading to gut dilation. Our work highlights the importance of UGs in schistosomes as promising targets for drug development in the treatment of the schistosomiasis.

Schistosoma japonicum↗
PubMed2006

Localization of binding sites in protein structures by optimization of a composite scoring function.

The rise in the number of functionally uncharacterized protein structures is increasing the demand for structure-based methods for functional annotation. Here, we describe a method for predicting the location of a binding site of a given type on a target protein structure. The method begins by constructing a scoring function, followed by a Monte Carlo optimization, to find a good scoring patch on the protein surface. The scoring function is a weighted linear combination of the z-scores of various properties of protein structure and sequence, including amino acid residue conservation, compactness, protrusion, convexity, rigidity, hydrophobicity, and charge density; the weights are calculated from a set of previously identified instances of the binding-site type on known protein structures. The scoring function can easily incorporate different types of information useful in localization, thus increasing the applicability and accuracy of the approach. To test the method, 1008 known protein structures were split into 20 different groups according to the type of the bound ligand. For nonsugar ligands, such as various nucleotides, binding sites were correctly identified in 55%-73% of the cases. The method is completely automated (http://salilab.org/patcher) and can be applied on a large scale in a structural genomics setting.

Amino Acid Sequence↗
PubMed2005

FSSA: a novel method for identifying functional signatures from structural alignments.

MOTIVATION: It is commonly believed that sequence determines structure, which in turn determines function. However, the presence of many proteins with the same structural fold but different functions suggests that global structure and function do not always correlate well. RESULTS: We propose a method for accurate functional annotation, based on identification of functional signatures from structural alignments (FSSA) using the Structural Classification of Proteins (SCOP) database. The FSSA method is superior at function discrimination and classification compared with several methods that directly inherit functional annotation information from homology inference, such as Smith-Waterman, PSI-BLAST, hidden Markov models and structure comparison methods, for a large number of structural fold families. Our results indicate that the contributions of amino acid residue types and positions to structure and function are largely separable for proteins in multi-functional fold families.

Algorithms↗
PubMed2005

Assessing the precision of high-throughput computational and laboratory approaches for the genome-wide identification of protein subcellular localization in bacteria.

BACKGROUND: Identification of a bacterial protein's subcellular localization (SCL) is important for genome annotation, function prediction and drug or vaccine target identification. Subcellular fractionation techniques combined with recent proteomics technology permits the identification of large numbers of proteins from distinct bacterial compartments. However, the fractionation of a complex structure like the cell into several subcellular compartments is not a trivial task. Contamination from other compartments may occur, and some proteins may reside in multiple localizations. New computational methods have been reported over the past few years that now permit much more accurate, genome-wide analysis of the SCL of protein sequences deduced from genomes. There is a need to compare such computational methods with laboratory proteomics approaches to identify the most effective current approach for genome-wide localization characterization and annotation. RESULTS: In this study, ten subcellular proteome analyses of bacterial compartments were reviewed. PSORTb version 2.0 was used to computationally predict the localization of proteins reported in these publications, and these computational predictions were then compared to the localizations determined by the proteomics study. By using a combined approach, we were able to identify a number of contaminants and proteins with dual localizations, and were able to more accurately identify membrane subproteomes. Our results allowed us to estimate the precision level of laboratory subproteome studies and we show here that, on average, recent high-precision computational methods such as PSORTb now have a lower error rate than laboratory methods. CONCLUSION: We have performed the first focused comparison of genome-wide proteomic and computational methods for subcellular localization identification, and show that computational methods have now attained a level of precision that is exceeding that of high-throughput laboratory approaches. We note that analysis of all cellular fractions collectively is required to effectively provide localization information from laboratory studies, and we propose an overall approach to genome-wide subcellular localization characterization that capitalizes on the complementary nature of current laboratory and computational methods.

Bacterial Proteins↗
PubMed2001

A functional update of the Escherichia coli K-12 genome.

BACKGROUND: Since the genome of Escherichia coli K-12 was initially annotated in 1997, additional functional information based on biological characterization and functions of sequence-similar proteins has become available. On the basis of this new information, an updated version of the annotated chromosome has been generated. RESULTS: The E. coli K-12 chromosome is currently represented by 4,401 genes encoding 116 RNAs and 4,285 proteins. The boundaries of the genes identified in the GenBank Accession U00096 were used. Some protein-coding sequences are compound and encode multimodular proteins. The coding sequences (CDSs) are represented by modules (protein elements of at least 100 amino acids with biological activity and independent evolutionary history). There are 4,616 identified modules in the 4,285 proteins. Of these, 48.9% have been characterized, 29.5% have an imputed function, 2.1% have a phenotype and 19.5% have no function assignment. Only 7% of the modules appear unique to E. coli, and this number is expected to be reduced as more genome data becomes available. The imputed functions were assigned on the basis of manual evaluation of functions predicted by BLAST and DARWIN analyses and by the MAGPIE genome annotation system. CONCLUSIONS: Much knowledge has been gained about functions encoded by the E. coli K-12 genome since the 1997 annotation was published. The data presented here should be useful for analysis of E. coli gene products as well as gene products encoded by other genomes.

Bacterial Proteins↗
PubMed2004

Structural proteomics: a tool for genome annotation.

In any newly sequenced genome, 30% to 50% of genes encode proteins with unknown molecular or cellular function. Fortunately, structural genomics is emerging as a powerful approach of functional annotation. Because of recent developments in high-throughput technologies, ongoing structural genomics projects are generating new structures at an unprecedented rate. In the past year, structural studies have identified many new structural motifs involved in enzymatic catalysis or in binding ligands or other macromolecules (DNA, RNA, protein). The efficiency by which function is deduced from structure can be further improved by the integration of structure with bioinformatics and other experimental approaches, such as screening for enzymatic activity or ligand binding.

DNA↗
PubMed2005

Clustering of domains of functionally related enzymes in the interaction database PRECISE by the generation of primary sequence patterns.

The PRECISE database was developed by our laboratory to allow for the systematic study of the ligand interactions common to a set of functionally related enzymes, where an interaction site is defined broadly as any residue(s) that interact with a ligand. During the construction of PRECISE, enzyme chains are extracted from the protein data bank (PDB) and clustered according to functional homology as defined by the enzyme commission (EC) nomenclature system. A sequence representative is chosen from each cluster based on the criterion set forth by the non-redundant PDB set, and pair-wise alignments of each cluster member to the representative are performed. Atom-based residue-ligand interactions are calculated for each cluster member, and the summation of ligand interactions for all cluster members at each aligned position is determined. Although we were able to successfully align most clusters using a simple dynamic programming algorithm, several cluster created exhibited poor pair-wise alignments of each cluster member to its sequence representative. We hypothesized that the observed alignment problems were, in most cases, due to the incorrect separation and alignment of different domains in multi-domain proteins, a mistake that frequently causes error proliferation in functional annotation. Here we present the results of generating primary sequence patterns for each poorly aligned cluster in PRECISE to assess the extent to which multi-domain proteins that are incorrectly aligned contributes to poor pair-wise alignments of each cluster member to its representative. This requires the use of an iterative locally optimal pair-wise alignment algorithm to build a hierarchical similarity-based sequence pattern for a set of functionally related enzymes. Our results show that poor alignments in PRECISE are caused most frequently by the misalignment of multi-domain proteins, and that the generation of primary sequence patterns for the assignment of sequence family membership yields better alignments for the functionally related enzyme clusters in PRECISE than our original alignment algorithm.

Amino Acid Sequence↗
PubMed2007

Searchlight on domains.

In this issue of Structure, examine in detail the functions of selected domains within proteins both when they are alone and when in combination with others. Domain function is relevant to molecular evolution and to annotation of proteins known only by sequence.

Enzymes↗
PubMed2025

Improving the Annotations of JCVI-Syn3a Proteins.

The JCVI-Syn3 organism is a minimal organism derived from Mycoplasma mycoides capri, which is capable of self-replication. While the ancestor has 863 genes, the synthetic progeny has only 473, with 434 of these coding for proteins. Despite initial efforts to understand all functions of the organism, a significant number of these protein-coding genes still have unknown functions, and subsequent studies have been only partially successful in elucidating their roles. In this study, we employ our innovative method PROST to identify homologs and better understand these previously unidentified genes. PROST employs protein language embeddings and enables the identification of remote homologs with as low as 16% sequence identity. PROST successfully finds functionally annotated homologs for 93% of the minimal genome with a high level of accuracy, both confirming previously identified functions, as well as proposing new functions for others. The results of our study can be accessed at https://bit.ly/prost-syn3a .

Molecular Sequence Annotation↗
PubMed2006

SynDB: a Synapse protein DataBase based on synapse ontology.

A synapse is the junction across which a nerve impulse passes from an axon terminal to a neuron, muscle cell or gland cell. The functions and building molecules of the synapse are essential to almost all neurobiological processes. To describe synaptic structures and functions, we have developed Synapse Ontology (SynO), a hierarchical representation that includes 177 terms with hundreds of synonyms and branches up to eight levels deep. associated 125 additional protein keywords and 109 InterPro domains with these SynO terms. Using a combination of automated keyword searches, domain searches and manual curation, we collected 14,000 non-redundant synapse-related proteins, including 3000 in human. We extensively annotated the proteins with information about sequence, structure, function, expression, pathways, interactions and disease associations and with hyperlinks to external databases. The data are stored and presented in the Synapse protein DataBase (SynDB, http://syndb.cbi.pku.edu.cn). SynDB can be interactively browsed by SynO, Gene Ontology (GO), domain families, species, chromosomal locations or Tribe-MCL clusters. It can also be searched by text (including Boolean operators) or by sequence similarity. SynDB is the most comprehensive database to date for synaptic proteins.

Animals↗
PubMed2004

Proteome-wide functional classification and identification of prokaryotic transmembrane proteins by transmembrane topology similarity comparison.

We propose a new method for classifying and identifying transmembrane (TM) protein functions in proteome-scale by applying a single-linkage clustering method based on TM topology similarity, which is calculated simply from comparing the lengths of loop regions. In this study, we focused on 87 prokaryotic TM proteomes consisting of 31 proteobacteria, 22 gram-positive bacteria, 19 other bacteria, and 15 archaea. Prior to performing the clustering, we first categorized individual TM protein sequences as "known," "putative" (similar to "known" sequences), or "unknown" by using the homology search and the sequence similarity comparison against SWISS-PROT to assess the current status of the functional annotation of the TM proteomes based on sequence similarity only. More than three-quarters, that is, 75.7% of the TM protein sequences are functionally "unknown," with only 3.8% and 20.5% of them being classified as "known" and "putative," respectively. Using our clustering approach based on TM topology similarity, we succeeded in increasing the rate of TM protein sequences functionally classified and identified from 24.3% to 60.9%. Obtained clusters correspond well to functional superfamilies or families, and the functional classification and identification are successfully achieved by this approach. For example, in an obtained cluster of TM proteins with six TM segments, 109 sequences out of 119 sequences annotated as "ATP-binding cassette transporter" are properly included and 122 "unknown" sequences are also contained.

Algorithms↗
PubMed2003

C. elegans ORFeome version 1.1: experimental verification of the genome annotation and resource for proteome-scale protein expression.

To verify the genome annotation and to create a resource to functionally characterize the proteome, we attempted to Gateway-clone all predicted protein-encoding open reading frames (ORFs), or the 'ORFeome,' of Caenorhabditis elegans. We successfully cloned approximately 12,000 ORFs (ORFeome 1.1), of which roughly 4,000 correspond to genes that are untouched by any cDNA or expressed-sequence tag (EST). More than 50% of predicted genes needed corrections in their intron-exon structures. Notably, approximately 11,000 C. elegans proteins can now be expressed under many conditions and characterized using various high-throughput strategies, including large-scale interactome mapping. We suggest that similar ORFeome projects will be valuable for other organisms, including humans.

Alternative Splicing↗
PubMed2004

Genome Properties: a system for the investigation of prokaryotic genetic content for microbiology, genome annotation and comparative genomics.

MOTIVATION: The presence or absence of metabolic pathways and structures provide a context that makes protein annotation far more reliable. Compiling such information across microbial genomes improves the functional classification of proteins and provides a valuable resource for comparative genomics. RESULTS: We have created a Genome Properties system to present key aspects of prokaryotic biology using standardized computational methods and controlled vocabularies. Properties reflect gene content, phenotype, phylogeny and computational analyses. The results of searches using hidden Markov models allow many properties to be deduced automatically, especially for families of proteins (equivalogs) conserved in function since their last common ancestor. Additional properties are derived from curation, published reports and other forms of evidence. Genome Properties system was applied to 156 complete prokaryotic genomes, and is easily mined to find differences between species, correlations between metabolic features and families of uncharacterized proteins, or relationships among properties. AVAILABILITY: Genome Properties can be found at http://www.tigr.org/Genome_Properties SUPPLEMENTARY INFORMATION: http://www.tigr.org/tigr-scripts/CMR2/genome_properties_references.spl.

Chromosome Mapping↗
PubMed2025

Chromosome-level genome assembly of Sinocyclocheilus jii based on PacBio HiFi and Hi-C sequencing.

Sinocyclocheilus jii, a cavefish species endemic to China, belongs to the genus Sinocyclocheilus within the family Cyprinidae. Species within this genus exhibit significant morphological differentiation, making it not only the most species-rich genus within Cyprinidae in China but also the most diverse group of cavefishes worldwide. However, the limited availability of genomic resources has limited investigations into the genetic basis of trait variations, phylogenetic relationships, and adaptive evolution in this genus. In this study, we assembled a chromosome-level reference genome for S. jii by integrating PacBio HiFi long reads, Illumina short reads, and Hi-C sequencing data. Flow cytometry was used to estimate the genome size prior to assembly, providing a key step in technical validation. The final genome assembly spans 1.75&#x2009;Gb with a contig N50 of 35.0&#x2009;Mb. Using Hi-C sequencing data, the assembled scaffolds were successfully anchored to 50 chromosomes. The completeness of the chromosome-level assembly was estimated at 98.9% by BUSCO analysis. Genome annotation identified 855.5&#x2009;Mb of repetitive sequences and predicted a total of 52,867 protein-coding genes, of which 51,932 genes were functionally annotated. This study presents a high-quality chromosome-level genome assembly and annotation of S. jii, providing a fundamental genomic resource for future phylogenetic and evolutionary studies.

Animals↗