Annotation In Public Databases Research Articles

Alternative promoters and splicing create multiple functionally distinct isoforms of oestrogen receptor alpha in breast cancer and healthy tissues.

Oestrogen receptor alpha (ER) is involved in cell growth and proliferation and functions as a transcription factor, a transcriptional coregulator, and in cytoplasmic signalling. It affects, for example, bone, endometrium, ovaries and mammary epithelium. It is a key biomarker in clinical management of breast cancer, where it is used as a prognostic and treatment-predictive factor, and a therapeutical target. Several ER isoforms have been described, but transcript annotation in public databases is incomplete and inconsistent, and functional differences are not well understood. We have analysed short- and long-read RNA sequencing data from breast tumours, breast cancer cell lines, and normal tissues to create a comprehensive annotation of ER transcripts and combined it with experimental studies of full-length protein and six alternative isoforms. The isoforms have varying transcription factor activity, subcellular localisation, and response to the ER-targeting drugs tamoxifen and fulvestrant. Antibodies differ in ability to detect alternative isoforms, which raises concerns for the interpretation of ER-status in routine pathology. Future work should investigate the effects of alternative isoforms on patient survival and therapy response. An accurate annotation of ER isoforms will aid in interpretation of clinical data and inform functional studies to improve our understanding of the ER in health and disease.

A chromosome-scale genome assembly of the Mongolian oak (Quercus mongolica).

Mongolian oak (Quercus mongolica Fisch.) is an ecologically and economically important white oak species native to and widespread in the temperate zone of East Asia. Here, we present a chromosome-scale reference genome assembly of Q.mongolica, a representative white oak species, by combining Illumina and PacBio data with Hi-C mapping technologies that is the first reference genome created for an Asian oak. Our results showed that the PacBio draft genome size was 809.84Mb, with a BUSCO complete gene percentage of 92.71%. Hi-C scaffolding anchored 774.59Mb contigs (95.65% of draft assembly) onto 12pseudochromosomes. The contig N50 and scaffold N50 were 2.64 and 66.74Mb, respectively. Of the 36,553 protein-coding genes predicted in the study, approximately 95% had functional annotations in public databases. A total of 435.34Mb (53.75% of the genome) of repetitive sequences were predicted in the assembled genome. Genome evolution analysis showed that Q.mongolica is closely related to Q.robur from Europe, and they shared a common ancestor ~11.8million years ago (Ma). Gene family evolution analysis of Q.mongolica revealed that the nucleotide-binding site (NBS)-encoding gene family related to disease resistance was significantly contracted, whereas the ECERIFERUM 1 (CER1) homologous genes related to cuticular wax biosynthesis was significantly expanded. This pioneering Asian oak genome resource represents an important supplement to the oak genomics community and will improve our understanding of Asian white oak biology and evolution.

Experimental and computational investigation of enzyme functional annotations uncovers misannotation in the EC 1.1.3.15 enzyme class.

Only a small fraction of genes deposited to databases have been experimentally characterised. The majority of proteins have their function assigned automatically, which can result in erroneous annotations. The reliability of current annotations in public databases is largely unknown; experimental attempts to validate the accuracy within individual enzyme classes are lacking. In this study we performed an overview of functional annotations to the BRENDA enzyme database. We first applied a high-throughput experimental platform to verify functional annotations to an enzyme class of S-2-hydroxyacid oxidases (EC 1.1.3.15). We chose 122 representative sequences of the class and screened them for their predicted function. Based on the experimental results, predicted domain architecture and similarity to previously characterised S-2-hydroxyacid oxidases, we inferred that at least 78% of sequences in the enzyme class are misannotated. We experimentally confirmed four alternative activities among the misannotated sequences and showed that misannotation in the enzyme class increased over time. Finally, we performed a computational analysis of annotations to all enzyme classes in the BRENDA database, and showed that nearly 18% of all sequences are annotated to an enzyme class while sharing no similarity or domain architecture to experimentally characterised representatives. We showed that even well-studied enzyme classes of industrial relevance are affected by the problem of functional misannotation.

Chromosome-level assembly of the mangrove plant Aegiceras corniculatum genome generated through Illumina, PacBio and Hi-C sequencing technologies.

Aegiceras corniculatum is a major mangrove plant species adapted to waterlogging and saline conditions, grows in the coastal intertidal zone of tropical and subtropical regions. Here, we present a chromosome-level genome assembly of A. corniculatum by incorporating PacBio long-read sequencing and Hi-C technology. The results showed that the PacBio draft genome size is 906.63Mb. Hi-C scaffolding anchored 885.06Mb contigs (97.62% of draft assembly) onto 24 pseudochromosomes. The contig N50 and scaffold N50 were 7.1Mb and 37.74Mb, respectively. Out of 40,727 protein-coding genes predicted in the study, 89% have functional annotations in public databases. We also showed that of the 603.93Mb repetitive sequences predicted in the assembled genome, long terminal repeat retrotransposons constitute 41.52%. The genome evolution analysis showed that the A. corniculatum genome experienced two whole-genome duplication events and shared the ancient γ whole-genome triplication event. A comparative genomic analysis revealed an incidence of expansion in 1,488 gene families associated with essential metabolism and biosynthetic pathways, including photosynthesis, oxidative phosphorylation, phenylalanine, glyoxylate, dicarboxylate metabolism, and DNA replication, which probably constitute adaptation traits that allow the A. corniculatum to survive in the intertidal zone. Also, the systematic characterization of genes associated with flavonoid biosynthesis pathway and the AcNHX gene family conducted in this study will provide insight into the adaptation mechanism of A. corniculatum to intertidal environments. The high-quality genome reported here can provide historical insights into genomic transformations that support the survival of A. corniculatum under harsh intertidal habitats.

Landscape of Eukaryotic Transmembrane Beta Barrel Proteins.

Even though in the last few years several families of eukaryotic β-barrel outer membrane proteins have been discovered, their computational characterization and their annotation in public databases are far from complete. The PFAM database includes only very few characteristic profiles for these families, and in most cases, the profile hidden Markov models (pHMMs) have been trained using prokaryotic and eukaryotic proteins together. Here, we present for the first time a comprehensive computational analysis of eukaryotic transmembrane β-barrels. Twelve characteristic pHMMs were built, based on an extensive literature search, which can discriminate eukaryotic β-barrels from other classes of proteins (globular and bacterial β-barrel ones), as well as between mitochondrial and chloroplastic ones. We built eight novel profiles for the chloroplastic β-barrel families that are not present in the PFAM database and also updated the profile for the MDM10 family (PF12519) in the PFAM database and divide the porin family (PF01459) into two separate families, namely, VDAC and TOM40.

The CaspBase: a curated database for evolutionary biochemical studies of caspase functional divergence and ancestral sequence inference.

Sequence databases are powerful tools for the contemporary scientists' toolkit. However, most functional annotations in public databases are determined computationally and are not verified by a human expert. While hypotheses generated from computational studies are now amenable to experimentation, the quality of the results relies on the quality of input data. We developed the CaspBase to expedite high-quality dataset compilation of annotated caspase sequences, to maximize phylogenetic signal, and to reduce the noise contributed from public databanks. We describe our methods of curation for the CaspBase and how researchers can acquire sequences from CaspBase.org. Our immediate goal for developing the CaspBase was to optimize the ancestral protein reconstruction (APR) of caspases, and we demonstrate the utility of the CaspBase in APR studies. We also developed the Common Position (CP) system for comparing human caspase family paralogs and suggest the CP system as an update to current reporting methods of caspase amino acid positions. We present a standardized multiple sequence alignment (MSA) for the CP system and show the advantage of using large databases such as the CaspBase in defining structural positions in proteins. Although the results described here pertain to caspase evolution and structure-function studies, the methods can be adapted to any gene family.

Analysis of the genomic basis of functional diversity in dinoflagellates using a transcriptome-based sequence similarity network.

Dinoflagellates are one of the most abundant and functionally diverse groups of eukaryotes. Despite an overall scarcity of genomic information for dinoflagellates, constantly emerging high-throughput sequencing resources can be used to characterize and compare these organisms. We assembled de novo and processed 46 dinoflagellate transcriptomes and used a sequence similarity network (SSN) to compare the underlying genomic basis of functional features within the group. This approach constitutes the most comprehensive picture to date of the genomic potential of dinoflagellates. A core-predicted proteome composed of 252 connected components (CCs) of putative conserved protein domains (pCDs) was identified. Of these, 206 were novel and 16 lacked any functional annotation in public databases. Integration of functional information in our network analyses allowed investigation of pCDs specifically associated with functional traits. With respect to toxicity, sequences homologous to those of proteins found in species with toxicity potential (e.g., sxtA4 and sxtG) were not specific to known toxin-producing species. Although not fully specific to symbiosis, the most represented functions associated with proteins involved in the symbiotic trait were related to membrane processes and ion transport. Overall, our SSN approach led to identification of 45,207 and 90,794 specific and constitutive pCDs of, respectively, the toxic and symbiotic species represented in our analyses. Of these, 56% and 57%, respectively (i.e., 25,393 and 52,193 pCDs), completely lacked annotation in public databases. This stresses the extent of our lack of knowledge, while emphasizing the potential of SSNs to identify candidate pCDs for further functional genomic characterization.

Comparative transcriptomic analysis indicates genes associated with local and systemic resistance to Colletotrichum graminicola in maize

The hemibiotrophic fungus Colletotrichum graminicola may cause severe damage to maize, affecting normal development of the plant and decreasing grain yield. In this context, understanding plant defense pathways at the inoculation site and systemically in uninoculated tissues can help in the development of genetic engineering of resistance against this pathogen. Previous work has discussed the molecular basis of maize - C. graminicola interaction. However, many genes involved in defense have not yet been exploited for lack of annotation in public databases. Here, changes in global gene expression were studied in root, male and female inflorescences of maize under local and systemic fungal infection treatments, respectively. RNA-Seq with qPCR was used to indicate genes involved in plant defense. We found that systemic acquired resistance induction in female inflorescences mainly involves accumulation of salicylic acid (SA)-inducible defense genes (ZmNAC, ZmHSF, ZmWRKY, ZmbZIP and PR1) and potential genes involved in chromatin modification. Furthermore, transcripts involved in jasmonic acid (JA) and ethylene (ET) signaling pathways were also accumulated and may participate in plant immunity. Moreover, several genes were functionally re-annotated based on domain signature, indicating novel candidates to be tested in strategies involving gene knockout and overexpression in plants.

Discovery of new protein families and functions: new challenges in functional metagenomics for biotechnologies and microbial ecology.

The rapid expansion of new sequencing technologies has enabled large-scale functional exploration of numerous microbial ecosystems, by establishing catalogs of functional genes and by comparing their prevalence in various microbiota. However, sequence similarity does not necessarily reflect functional conservation, since just a few modifications in a gene sequence can have a strong impact on the activity and the specificity of the corresponding enzyme or the recognition for a sensor. Similarly, some microorganisms harbor certain identified functions yet do not have the expected related genes in their genome. Finally, there are simply too many protein families whose function is not yet known, even though they are highly abundant in certain ecosystems. In this context, the discovery of new protein functions, using either sequence-based or activity-based approaches, is of crucial importance for the discovery of new enzymes and for improving the quality of annotation in public databases. This paper lists and explores the latest advances in this field, along with the challenges to be addressed, particularly where microfluidic technologies are concerned.

Archaeal Clusters of Orthologous Genes (arCOGs): An Update and Application for Analysis of Shared Features between Thermococcales, Methanococcales, and Methanobacteriales.

With the continuously accelerating genome sequencing from diverse groups of archaea and bacteria, accurate identification of gene orthology and availability of readily expandable clusters of orthologous genes are essential for the functional annotation of new genomes. We report an update of the collection of archaeal Clusters of Orthologous Genes (arCOGs) to cover, on average, 91% of the protein-coding genes in 168 archaeal genomes. The new arCOGs were constructed using refined algorithms for orthology identification combined with extensive manual curation, including incorporation of the results of several completed and ongoing research projects in archaeal genomics. A new level of classification is introduced, superclusters that unit two or more arCOGs and more completely reflect gene family evolution than individual, disconnected arCOGs. Assessment of the current archaeal genome annotation in public databases indicates that consistent use of arCOGs can significantly improve the annotation quality. In addition to their utility for genome annotation, arCOGs also are a platform for phylogenomic analysis. We explore this aspect of arCOGs by performing a phylogenomic study of the Thermococci that are traditionally viewed as the basal branch of the Euryarchaeota. The results of phylogenomic analysis that involved both comparison of multiple phylogenetic trees and a search for putative derived shared characters by using phyletic patterns extracted from the arCOGs reveal a likely evolutionary relationship between the Thermococci, Methanococci, and Methanobacteria. The arCOGs are expected to be instrumental for a comprehensive phylogenomic study of the archaea.

Genome-scale identification and characterization of moonlighting proteins.

BackgroundMoonlighting proteins perform two or more cellular functions, which are selected based on various contexts including the cell type they are expressed, their oligomerization status, and the binding of different ligands at different sites. To understand overall landscape of their functional diversity, it is important to establish methods that can identify moonlighting proteins in a systematic fashion. Here, we have developed a computational framework to find moonlighting proteins on a genome scale and identified multiple proteomic characteristics of these proteins.ResultsFirst, we analyzed Gene Ontology (GO) annotations of known moonlighting proteins. We found that the GO annotations of moonlighting proteins can be clustered into multiple groups reflecting their diverse functions. Then, by considering the observed GO term separations, we identified 33 novel moonlighting proteins in Escherichia coli and confirmed them by literature review. Next, we analyzed moonlighting proteins in terms of protein-protein interaction, gene expression, phylogenetic profile, and genetic interaction networks. We found that moonlighting proteins physically interact with a higher number of distinct functional classes of proteins than non-moonlighting ones and also found that most of the physically interacting partners of moonlighting proteins share the latter’s primary functions. Interestingly, we also found that moonlighting proteins tend to interact with other moonlighting proteins. In terms of gene expression and phylogenetically related proteins, a weak trend was observed that moonlighting proteins interact with more functionally diverse proteins. Structural characteristics of moonlighting proteins, i.e. intrinsic disordered regions and ligand binding sites were also investigated.ConclusionAdditional functions of moonlighting proteins are difficult to identify by experiments and these proteins also pose a significant challenge for computational function annotation. Our method enables identification of novel moonlighting proteins from current functional annotations in public databases. Moreover, we showed that potential moonlighting proteins without sufficient functional annotations can be identified by analyzing available omics-scale data. Our findings open up new possibilities for investigating the multi-functional nature of proteins at the systems level and for exploring the complex functional interplay of proteins in a cell.ReviewersThis article was reviewed by Michael Galperin, Eugine Koonin, and Nick Grishin.Electronic supplementary materialThe online version of this article (doi:10.1186/s13062-014-0030-9) contains supplementary material, which is available to authorized users.

Genome-scale identification and characterization of moonlighting proteins

Moonlighting proteins perform two or more cellular functions, which are selected based on various contexts including the cell type they are expressed, their oligomerization status, and the binding of different ligands at different sites. To understand overall landscape of their functional diversity, it is important to establish methods that can identify moonlighting proteins in a systematic fashion. Here, we have developed a computational framework to find moonlighting proteins on a genome scale and identified multiple proteomic characteristics of these proteins. First, we analyzed Gene Ontology (GO) annotations of known moonlighting proteins. We found that the GO annotations of moonlighting proteins can be clustered into multiple groups reflecting their diverse functions. Then, by considering the observed GO term separations, we identified 33 novel moonlighting proteins in Escherichia coli and confirmed them by literature review. Next, we analyzed moonlighting proteins in terms of protein-protein interaction, gene expression, phylogenetic profile, and genetic interaction networks. We found that moonlighting proteins physically interact with a higher number of distinct functional classes of proteins than non-moonlighting ones and also found that most of the physically interacting partners of moonlighting proteins share the latter’s primary functions. Interestingly, we also found that moonlighting proteins tend to interact with other moonlighting proteins. In terms of gene expression and phylogenetically related proteins, a weak trend was observed that moonlighting proteins interact with more functionally diverse proteins. Structural characteristics of moonlighting proteins, i.e. intrinsic disordered regions and ligand binding sites were also investigated. Additional functions of moonlighting proteins are difficult to identify by experiments and these proteins also pose a significant challenge for computational function annotation. Our method enables identification of novel moonlighting proteins from current functional annotations in public databases. Moreover, we showed that potential moonlighting proteins without sufficient functional annotations can be identified by analyzing available omics-scale data. Our findings open up new possibilities for investigating the multi-functional nature of proteins at the systems level and for exploring the complex functional interplay of proteins in a cell. This article was reviewed by Michael Galperin, Eugine Koonin, and Nick Grishin.

A genome-wide analysis of annexins from parasitic organisms and their vectors

In this study, we conduct an in-depth analysis of annexin proteins from a diverse range of invertebrate taxa, including the major groups that contain the parasites and vector organisms that are harmful to humans and domestic animals. Using structure-based amino acid sequence alignments and phylogenetic analyses, we present a classification for this protein group and assign names to sequences with ambiguous annotations in public databases. Our analyses reveal six distinct annexin clades, and the mapping of genes encoding annexins to the genome of the human blood fluke Schistosoma mansoni supports the hypothesis of gene duplication as a major evolutionary event in annexin genesis. This study illuminates annexin diversity from a novel perspective using contemporary phylogenetic hypotheses of eukaryote evolution, and will aid the consolidation of annexin protein identities in public databases and provide a foundation for future functional analysis and characterisation of these proteins in parasites of socioeconomic importance.

Re-Annotation of Two Hyperthermophilic Archaea Pyrococcus abyssi GE5 and Pyrococcus furiosus DSM 3638

Pyrococcus abyssi GE5 (P. aby) and Pyrococcus furiosus DSM 3638 (P. fur) are two model hyperthermophilic archaea. However, their annotations in public databases are unsatisfactory. In this article, the two genomes were re-annotated according to the following steps. (i) All "hypothetical genes" in the original annotation were re-identified based on the Z-curve method, and some of them were recognized as non-coding open reading frames (ORFs). Evidence showed that the recognized non-coding ORFs were highly unlikely to encode proteins. (ii) The translation initiation sites (TISs) of all the annotated genes were re-located, and more than 10% of the TISs were shifted to 5'-upstream or 3'-downstream regions. (iii) The functions of the refined "hypothetical genes" were predicted using sequence alignment tools, more than 200 originally annotated "hypothetical genes" in either of the two hyperthermophiles were assigned functions. A large number of these functions have reference support or experimentally characterized homologues. All the refined information will serve as a valuable resource for research on P. aby and P. fur, which may be helpful in the exploration of thermal adaptation mechanisms. The complete re-annotation files of P. aby and P. fur are available at http://211.69.128.148/download/ .

Automatic rule generation for protein annotation with the C4.5 data mining algorithm applied on SWISS-PROT.

The gap between the amount of newly submitted protein data and reliable functional annotation in public databases is growing. Traditional manual annotation by literature curation and sequence analysis tools without the use of automated annotation systems is not able to keep up with the ever increasing quantity of data that is submitted. Automated supplements to manually curated databases such as TrEMBL or GenPept cover raw data but provide only limited annotation. To improve this situation automatic tools are needed that support manual annotation, automatically increase the amount of reliable information and help to detect inconsistencies in manually generated annotations. A standard data mining algorithm was successfully applied to gain knowledge about the Keyword annotation in SWISS-PROT. 11 306 rules were generated, which are provided in a database and can be applied to yet unannotated protein sequences and viewed using a web browser. They rely on the taxonomy of the organism, in which the protein was found and on signature matches of its sequence. The statistical evaluation of the generated rules by cross-validation suggests that by applying them on arbitrary proteins 33% of their keyword annotation can be generated with an error rate of 1.5%. The coverage rate of the keyword annotation can be increased to 60% by tolerating a higher error rate of 5%. The results of the automatic data mining process can be browsed on http://golgi.ebi.ac.uk:8080/Spearmint/ Source code is available upon request. kretsch@ebi.ac.uk.

Arabidopsis thaliana gene expression microarray services

Incyte has developed a new gene expression microarray (GEM) for analysis of the plant functional genomic system Arabidopsis thaliana. This GEM features over 7,000 array elements from a non-redundant cDNA collection; nearly 30% of the estimated 25,000 genes in this organism. Over 2,000 of these clones represent genes that have functional annotation in public databases. We are offering hybridization and analysis services for the Arabidopsis GEM via Incyte and Genome Systems. Arabidopsis is the primary model system for the study of dicot plant genomics. Academic and commercial groups are using the combination of genomic and genetic tools available for Arabidopsis to study complex problems in plant biology. We have performed a few biological studies using the Arabidopsis GEM to validate the platform and provide examples of possible applications. We will present sample data on these studies.