Proteome Sequences Research Articles

Genetic and Proteomic Sequence Analysis for the Theoretical Prediction of O-Glycosylation Sites in Proteins

O-glycosylation is one of the most requisite and ubiquitous protein post translational modification by which the oligosaccharides are conjugated to polypeptide backbone at specific sites. Proteins involved in this modification are synthesized as encoded by their genetic information and the function of the glycoprotein is determined by the O-glycosylated sites and the conjugated glycans. The identification of O-glycosylation sites has been developing rapidly in recent years both by experimental and theoretical studies. In the present study, we adopted a method to predict O-glycosylation site by integrating genetic and proteomic sequence information. Data for the analysis are taken from O-GlycBase v6.0, EMBL-EBI and UniprotKB/Swissprot databases. The prediction is carried out on the collected datasets by following jack-knife procedure. As there is no predefined consensus motif identified for O-glycosylation, the preference of amino acids and codons within the window size of -3 to +3 positions of the glycosylated sites are computed. The analysis reveals the preference of specific codons and amino acids around the glycosylated sites. A prediction program is developed to identify the sites of glycosylation based on the preferences of codons and amino acids. Sensitivity, specificity and accuracy of our prediction method are 91%, 78% and 86% respectively. In order to access our prediction, a comparative study is carried out on prediction with some of the publically available online predictors. It resulted in high predictive performance. In addition to amino acids, preference of certain codons around the glycosylated sites might play a role in the glycosylability of glycoproteins and the methodology could be extended to study other such modifications in proteins to gain better insights.

Livebearing or egg-laying mammals: 27 decisive nucleotides of FAM168.

In the present study, we determine comprehensive molecular phylogenetic relationships of the novel myelin-associated neurite-outgrowth inhibitor (MANI) gene across the entire eukaryotic lineage. Combined computational genomic and proteomic sequence analyses revealed MANI as one of the two members of the novel family with sequence similarity 168 member (FAM168) genes, consisting of FAM168A and FAM168B, having distinct genetic differences that illustrate diversification in its biological function and genetic taxonomy across the phylogenetic tree. Phylogenetic analyses based on coding sequences of these FAM168 genes revealed that they are paralogs and that the earliest emergence of these genes occurred in jawed vertebrates such as Callorhinchus milii. Surprisingly, these two genes are absent in other chordates that have a notochord at some stage in their lives, such as branchiostoma and tunicates. In the context of phylogenetic relationships among eukaryotic species, our results demonstrate the presence of FAM168 orthologs in vertebrates ranging from Callorhinchus milii to Homo sapiens, displaying distinct taxonomic clusters, comprised of fish, amphibians, reptiles, birds, and mammals. Analyses of individual FAM168 exons in our sample provide new insights into the molecular relationships between FAM168A and FAM168B (MANI) on the one hand and livebearing and egg-laying mammals on the other hand, demonstrating that a distinctive intermediate exon 4, comprised of 27 nucleotides, appears suddenly only in FAM168A and there in the livebearing mammals only but is absent from all other species including the egg-laying mammals.

Opposite Electron-Transfer Dissociation and Higher-Energy Collisional Dissociation Fragmentation Characteristics of Proteolytic K/R(X)n and (X)nK/R Peptides Provide Benefits for Peptide Sequencing in Proteomics and Phosphoproteomics.

A key step in shotgun proteomics is the digestion of proteins into peptides amenable for mass spectrometry. Tryptic peptides can be readily sequenced and identified by collision-induced dissociation (CID) or higher-energy collisional dissociation (HCD) because the fragmentation rules are well-understood. Here, we investigate LysargiNase, a perfect trypsin mirror protease, because it cleaves equally specific at arginine and lysine residues, albeit at the N-terminal end. LysargiNase peptides are therefore practically tryptic-like in length and sequence except that following ESI, the two protons are now both positioned at the N-terminus. Here, we compare side-by-side the chromatographic separation properties, gas-phase fragmentation characteristics, and (phospho)proteome sequence coverage of tryptic (i.e., (X)nK/R) and LysargiNase (i.e., K/R(X)n) peptides using primarily electron-transfer dissociation (ETD) and, for comparison, HCD. We find that tryptic and LysargiNase peptides fragment nearly as mirror images. For LysargiNase predominantly N-terminal peptide ions (c-ions (ETD) and b-ions (HCD)) are formed, whereas for trypsin, C-terminal fragment ions dominate (z-ions (ETD) and y-ions (HCD)) in a homologous mixture of complementary ions. Especially during ETD, LysargiNase peptides fragment into low-complexity but information-rich sequence ladders. Trypsin and LysargiNase chart distinct parts of the proteome, and therefore, the combined use of these enzymes will benefit a more in-depth and reliable analysis of (phospho)proteomes.

UniProt: the universal protein knowledgebase.

The UniProt knowledgebase is a large resource of protein sequences and associated detailed annotation. The database contains over 60 million sequences, of which over half a million sequences have been curated by experts who critically review experimental and predicted data for each protein. The remainder are automatically annotated based on rule systems that rely on the expert curated knowledge. Since our last update in 2014, we have more than doubled the number of reference proteomes to 5631, giving a greater coverage of taxonomic diversity. We implemented a pipeline to remove redundant highly similar proteomes that were causing excessive redundancy in UniProt. The initial run of this pipeline reduced the number of sequences in UniProt by 47 million. For our users interested in the accessory proteomes, we have made available sets of pan proteome sequences that cover the diversity of sequences for each species that is found in its strains and sub-strains. To help interpretation of genomic variants, we provide tracks of detailed protein information for the major genome browsers. We provide a SPARQL endpoint that allows complex queries of the more than 22 billion triples of data in UniProt (http://sparql.uniprot.org/). UniProt resources can be accessed via the website at http://www.uniprot.org/.

Designing of Epitope-Focused Vaccine by Targeting E6 and E7 Conserved Protein Sequences: An Immuno-Informatics Approach in Human Papillomavirus 58 Isolates.

Human papillomavirus (HPV) is a DNA virus that belongs to the papillomavirus family and is capable of infecting humans. Currently, few vaccines are available to prevent infection by HPV. However, they are not so much effective and provide little benefit to women who have already been infected with HPV. The aim of this study was to design epitope-based vaccines of HPV58 by targeting E6 and E7 proteins of HPV58. Proteomic sequences were retrieved from different isolates at different time periods and later analyzed by performing alignment of these sequences. To ensure the capacity of humoral and cell-mediated immunity, both B cell and T cell immunity were checked for the peptides. For E6 protein, the peptide sequence from 48 to 54 amino acids and one 9-m epitope ETSVHEIEL were the most potential B cell and T cell epitopes, respectively. This peptide could interact with as many as eight MHC-1 alleles and showed high population coverage up to 90.31%. On the other hand, the peptide region for the E7 protein ranged from 27 to 33 amino acids and two 9-m epitopes QAQPATANY, SSDEDEIGL were found as the most potential B cell and T cell epitopes, respectively. The peptide sequences could interact with as many as seven MHC-1 alleles and showed population coverage up to 90.31%. Furthermore, conservancy analysis was also performed using in silico tools and showed a conservancy of 100% for all the selected epitopes. In addition to this, the allergenicity of the epitopes was also evaluated. Although the study requires further in vitro and in vivo screening, this epitope-focused peptide vaccine designing opens up a new skyline that holds a prospective future in HPV research.

A new method for studying the evolutionary origin of the SAR11 clade marine bacteria

The free-living SAR11 clade is a globally abundant group of oceanic Alphaproteobacteria, with small genome sizes and rich genomic A+T content. However, the taxonomy of SAR11 has become controversial recently. Some researchers argue that the position of SAR11 is a sister group to Rickettsiales. Other researchers advocate that SAR11 is located within free-living lineages of Alphaproteobacteria. Here, we use the natural vector representation method to identify the evolutionary origin of the SAR11 clade. This alignment-free method does not depend on any model assumptions. With this approach, the correspondence between proteome sequences and their natural vectors is one-to-one. After fixing a set of proteins, each bacterium is represented by a set of vectors. The Hausdorff distance is then used to compute the dissimilarity distance between two bacteria. The phylogenetic tree can be reconstructed based on these distances. Using our method, we systematically analyze four data sets of alphaproteobacterial proteomes in order to reconstruct the phylogeny of Alphaproteobacteria. From this we can see that the phylogenetic position of the SAR11 group is within a group of other free-living lineages of Alphaproteobacteria.

Proteomic analysis of the medicinal plant Artemisia annua: Data from leaf and trichome extracts.

This article contains raw and processed data related to research published by Bryant et al.[1]. Data was obtained by MS-based proteomics, analysing trichome-enriched, trichome-depleted and whole leaf samples taken from the medicinal plant Artemisia annua and searching the acquired MS/MS data against a recently published contig database [2] and other genomic and proteomic sequence databases for comparison. The processed data shows that an order-of-magnitude more proteins have been identified from trichome-enriched Artemisia annua samples in comparison to previously published data. Proteins known to have a role in the biosynthesis of artemisinin and other highly abundant proteins were found which imply additional enzymatically driven processes occurring within the trichomes that are significant for the biosynthesis of artemisinin.

Core Proteomic Analysis of Unique Metabolic Pathways of Salmonella enterica for the Identification of Potential Drug Targets.

BackgroundInfections caused by Salmonella enterica, a Gram-negative facultative anaerobic bacteria belonging to the family of Enterobacteriaceae, are major threats to the health of humans and animals. The recent availability of complete genome data of pathogenic strains of the S. enterica gives new avenues for the identification of drug targets and drug candidates. We have used the genomic and metabolic pathway data to identify pathways and proteins essential to the pathogen and absent from the host.MethodsWe took the whole proteome sequence data of 42 strains of S. enterica and Homo sapiens along with KEGG-annotated metabolic pathway data, clustered proteins sequences using CD-HIT, identified essential genes using DEG database and discarded S. enterica homologs of human proteins in unique metabolic pathways (UMPs) and characterized hypothetical proteins with SVM-prot and InterProScan. Through this core proteomic analysis we have identified enzymes essential to the pathogen.ResultsThe identification of 73 enzymes common in 42 strains of S. enterica is the real strength of the current study. We proposed all 73 unexplored enzymes as potential drug targets against the infections caused by the S. enterica. The study is comprehensive around S. enterica and simultaneously considered every possible pathogenic strain of S. enterica. This comprehensiveness turned the current study significant since, to the best of our knowledge it is the first subtractive core proteomic analysis of the unique metabolic pathways applied to any pathogen for the identification of drug targets. We applied extensive computational methods to shortlist few potential drug targets considering the druggability criteria e.g. Non-homologous to the human host, essential to the pathogen and playing significant role in essential metabolic pathways of the pathogen (i.e. S. enterica). In the current study, the subtractive proteomics through a novel approach was applied i.e. by considering only proteins of the unique metabolic pathways of the pathogens and mining the proteomic data of all completely sequenced strains of the pathogen, thus improving the quality and application of the results. We believe that the sharing of the knowledge from this study would eventually lead to bring about novel and unique therapeutic regimens against the infections caused by the S. enterica.

Low Temperature Adaptation Is Not the Opposite Process of High Temperature Adaptation in Terms of Changes in Amino Acid Composition.

Previous studies focused on psychrophilic adaptation generally have demonstrated that multiple mechanisms work together to increase protein flexibility and activity, as well as to decrease the thermostability of proteins. However, the relationship between high and low temperature adaptations remains unclear. To investigate this issue, we collected the available predicted whole proteome sequences of species with different optimal growth temperatures, and analyzed amino acid variations and substitutional asymmetry in pairs of homologous proteins from related species. We found that changes in amino acid composition associated with low temperature adaptation did not exhibit a coherent opposite trend when compared with changes in amino acid composition associated with high temperature adaptation. This result indicates that during their evolutionary histories the proteome-scale evolutionary patterns associated with prokaryotes exposed to low temperature environments were distinct from the proteome-scale evolutionary patterns associated with prokaryotes exposed to high temperature environments in terms of changes in amino acid composition of the proteins.

Nucleotide binding database NBDB--a collection of sequence motifs with specific protein-ligand interactions.

NBDB database describes protein motifs, elementary functional loops (EFLs) that are involved in binding of nucleotide-containing ligands and other biologically relevant cofactors/coenzymes, including ATP, AMP, ATP, GMP, GDP, GTP, CTP, PAP, PPS, FMN, FAD(H), NAD(H), NADP, cAMP, cGMP, c-di-AMP and c-di-GMP, ThPP, THD, F-420, ACO, CoA, PLP and SAM. The database is freely available online at http://nbdb.bii.a-star.edu.sg. In total, NBDB contains data on 249 motifs that work in interactions with 24 ligands. Sequence profiles of EFL motifs were derived de novo from nonredundant Uniprot proteome sequences. Conserved amino acid residues in the profiles interact specifically with distinct chemical parts of nucleotide-containing ligands, such as nitrogenous bases, phosphate groups, ribose, nicotinamide, and flavin moieties. Each EFL profile in the database is characterized by a pattern of corresponding ligand–protein interactions found in crystallized ligand–protein complexes. NBDB database helps to explore the determinants of nucleotide and cofactor binding in different protein folds and families. NBDB can also detect fragments that match to profiles of particular EFLs in the protein sequence provided by user. Comprehensive information on sequence, structures, and interactions of EFLs with ligands provides a foundation for experimental and computational efforts on design of required protein functions.

Prediction of Ionizing Radiation Resistance in Bacteria Using a Multiple Instance Learning Model.

Ionizing-radiation-resistant bacteria (IRRB) are important in biotechnology. In this context, in silico methods of phenotypic prediction and genotype-phenotype relationship discovery are limited. In this work, we analyzed basal DNA repair proteins of most known proteome sequences of IRRB and ionizing-radiation-sensitive bacteria (IRSB) in order to learn a classifier that correctly predicts this bacterial phenotype. We formulated the problem of predicting bacterial ionizing radiation resistance (IRR) as a multiple-instance learning (MIL) problem, and we proposed a novel approach for this purpose. We provide a MIL-based prediction system that classifies a bacterium to either IRRB or IRSB. The experimental results of the proposed system are satisfactory with 91.5% of successful predictions.

GoFDR: A sequence alignment based method for predicting protein functions

In this study, we developed a method named GoFDR for predicting Gene Ontology (GO)-based protein functions. The input for GoFDR is simply a query sequence-based multiple sequence alignment (MSA) produced by PSI-BLAST. For each GO term annotated to the sequences in the MSA, GoFDR identifies a number of functionally discriminating residues (FDRs) specific to the GO term, and scores the query sequence using a position specific scoring matrix (PSSM) constructed for the FDRs. The raw score is then converted into a probability score according to a score-to-probability table prepared from training sequences. GoFDR outperformed three sequence-based methods for predicting GO functions in a benchmark of 18,520 sequences. In addition, GoFDR was ranked one of the top methods according to the preliminary evaluation report released by the 2nd Critical Assessment of Function Annotation (CAFA2) project. Finally, we applied GoFDR to the complete human proteome sequences, and showed that the predictions made by GoFDR with high confidence significantly expanded current annotations of human proteome. As such, GoFDR is of great value not only for annotating protein functions in newly sequenced genomes, but also for characterizing the function of proteins of interest.

Proteomic analysis of Artemisia annua--towards elucidating the biosynthetic pathways of the antimalarial pro-drug artemisinin.

BackgroundMS-based proteomics was applied to the analysis of the medicinal plant Artemisia annua, exploiting a recently published contig sequence database (Graham et al. (2010) Science 327, 328–331) and other genomic and proteomic sequence databases for comparison. A. annua is the predominant natural source of artemisinin, the precursor for artemisinin-based combination therapies (ACTs), which are the WHO-recommended treatment for P. falciparum malaria.ResultsThe comparison of various databases containing A. annua sequences (NCBInr/viridiplantae, UniProt/viridiplantae, UniProt/A. annua, an A. annua trichome Trinity contig database, the above contig database and another A. annua EST database) revealed significant differences in respect of their suitability for proteomic analysis, showing that an organism-specific database that has undergone extensive curation, leading to longer contig sequences, can greatly increase the number of true positive protein identifications, while reducing the number of false positives. Compared to previously published data an order-of-magnitude more proteins have been identified from trichome-enriched A. annua samples, including proteins which are known to be involved in the biosynthesis of artemisinin, as well as other highly abundant proteins, which suggest additional enzymatic processes occurring within the trichomes that are important for the biosynthesis of artemisinin.ConclusionsThe newly gained information allows for the possibility of an enzymatic pathway, utilizing peroxidases, for the less well understood final stages of artemisinin’s biosynthesis, as an alternative to the known non-enzymatic in vitro conversion of dihydroartemisinic acid to artemisinin. Data are available via ProteomeXchange with identifier PXD000703.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-015-0565-7) contains supplementary material, which is available to authorized users.

RWD Domain as an E2 (Ubc9)-Interaction Module

An RWD domain is a well conserved domain found through bioinformatic analysis of the human proteome sequence; however, its function has been unknown. Ubiquitin-like modifications require the catalysis of three enzymes generally known as E1, E2, and E3. We solved the crystal structure of the E2 for the small ubiquitin-like modifiers (SUMO) in complex with an RWD domain and confirmed the structure using solution NMR analysis. The binding surface of RWD on Ubc9 is located near the N terminus of Ubc9 that is known to be involved in noncovalent binding of the proteins in the conjugation machinery, including a domain of E1, SUMO, and an E3 ligase. NMR data indicate that the RWD domain does not bind to SUMO and E1. The interaction between RWD and Ubc9 has a Kd of 32 ± 4 μM. Consistent with the structure and binding affinity and in contrast to a previous report, the RWD domain and RWDD3 have minimal effects on global SUMOylation. The structural and biochemical information presented here forms the basis for further investigation of the functions of RWD-containing proteins.

Test and Evaluation of ff99IDPs Force Field for Intrinsically Disordered Proteins.

Over 40% of eukaryotic proteomic sequences have been predicted to be intrinsically disordered proteins (IDPs) or intrinsically disordered regions (IDRs) and confirmed to be associated with many diseases. However, widely used force fields cannot well reproduce the conformers of IDPs. Previously the ff99IDPs force field was released to simulate IDPs with CMAP energy corrections for the eight disorder-promoting residues. In order to further confirm the performance of ff99IDPs, three representative IDP systems (arginine-rich HIV-1 Rev, aspartic proteinase inhibitor IA3, and α-synuclein) were used to test and evaluate the simulation results. The results show that for free disordered proteins, the chemical shifts from the ff99IDPs simulations are in quantitative agreement with those from reported NMR measurements and better than those from ff99SBildn. Thus, ff99IDPs can sample more clusters of disordered conformers than ff99SBildn. For structural proteins, both ff99IDPs and ff99SBildn can well reproduce the conformations. In general, ff99IDPs can successfully be used to simulate the conformations of IDPs and IDRs in both bound and free states. However, relative errors could still be found at the boundaries of ordered residues scattered in long disorder-promoting sequences. Therefore, polarizable force fields might be one of the possible ways to further improve the performance on IDPs.

Proteomics beyond trypsin.

Peptide-centered shotgun analysis of proteins has been the core technology in mass spectrometry based proteomics and has enabled numerous biological discoveries, such as the large-scale charting of protein-protein interaction networks, the quantitative analysis of protein post-translational modifications and even the first drafts of the human proteome. The conversion of proteins into peptides in these so-called bottom-up approaches is nearly uniquely done by using trypsin as a proteolytic reagent. Here, we argue that our view of the proteome still remains incomplete and this is partially due to the nearly exclusive use of trypsin. Newly emerging alternative proteases and/or multi-protease protein digestion aim to increase proteome sequence coverage and improve the identification of post-translational modifications, through the analysis of complementary and often longer peptides, introducing an approach termed middle-down proteomics. Of pivotal importance for this purpose is the identification of proteases beneficial for use in proteomics. Here, we describe some of the shortcomings of the nearly exclusive use of trypsin in proteomics and review the properties of other proteomics-appropriate proteases. We describe favorable protease traits with an emphasis on middle-down proteomics and suggest potential sources for the discovery of new proteases. We also highlight a few examples wherein the use of other proteases than trypsin enabled the generation of more comprehensive data sets leading to previously unexplored knowledge of the proteome.

Equivalent genomic (proteomic) sequences and semigroups

We discuss some combinatorial properties of genomic and proteomic sequences and propose semigroup theory as a versatile algebraic method for their study. In particular, we consider biologically equivalent but not identical sequences and finding hidden regularities therein.

The cerebrospinal fluid immunoglobulin transcriptome and proteome in neuromyelitis optica reveals central nervous system-specific B cell populations.

BackgroundNeuromyelitis optica (NMO) is a severe demyelinating disorder of the central nervous system (CNS) associated with the presence of an autoimmune antibody response (AQP4-IgG) against the water channel aquaporin-4 (AQP4). It remains unclear whether pathologic AQP4-IgG in the CNS is produced entirely by peripheral plasma cells or is generated in part by infiltrating B cells. To determine the overlap of AQP4-IgG idiotypes between the CNS and periphery, we compared the immunoglobulin G (IgG) transcriptome of cerebrospinal fluid (CSF) plasmablasts with the CSF and serum IgG proteomes in 7 AQP4-seropositive NMO patients following exacerbation.MethodsCSF variable region Ig heavy- (VH) and light-chain (VL) transcriptome libraries were generated for each patient from CSF plasmablasts by single cell sorting, reverse transcriptase polymerase chain reaction (RT-PCR), and DNA sequencing. Recombinant antibodies were generated from clonally expanded, paired VH and VL sequences and tested for AQP4-reactivity by cell-binding assay. CSF and serum IgG fractions were searched for sequences that matched their respective CSF IgG transcriptome. Matching peptides within the same patient’s CSF and serum IgG proteomes were also identified.ResultsIn each NMO patient, we recovered CSF IgG VH and VL sequences that matched germline-mutated IgG protein sequences from the patient’s CSF and serum IgG proteomes. Although a modest variation was observed between patients, the overlap between the transcriptome and proteome sequences was found primarily, but not exclusively, within the CSF. More than 50% of the CSF IgG transcriptome sequences were exclusively found in the CSF IgG proteome, whereas 28% were found in both the CSF and blood IgG proteome, and 18% were found exclusively in the blood proteome. A comparable distribution was noted when only AQP4-specific IgG clones were considered. Similarly, on average, only 50% of the CSF IgG proteome matched corresponding peptide sequences in the serum.ConclusionsDuring NMO exacerbations, a substantial fraction of the intrathecal Ig proteome is generated by an intrathecal B cell population composed of both novel and peripherally-derived clones. Intrathecal CSF B cell clones may contribute to NMO disease exacerbation and lesion formation and may be an important target for preventative therapies.

Transmitted Virus Fitness and Host T Cell Responses Collectively Define Divergent Infection Outcomes in Two HIV-1 Recipients

Control of virus replication in HIV-1 infection is critical to delaying disease progression. While cellular immune responses are a key determinant of control, relatively little is known about the contribution of the infecting virus to this process. To gain insight into this interplay between virus and host in viral control, we conducted a detailed analysis of two heterosexual HIV-1 subtype A transmission pairs in which female recipients sharing three HLA class I alleles exhibited contrasting clinical outcomes: R880F controlled virus replication while R463F experienced high viral loads and rapid disease progression. Near full-length single genome amplification defined the infecting transmitted/founder (T/F) virus proteome and subsequent sequence evolution over the first year of infection for both acutely infected recipients. T/F virus replicative capacities were compared in vitro, while the development of the earliest cellular immune response was defined using autologous virus sequence-based peptides. The R880F T/F virus replicated significantly slower in vitro than that transmitted to R463F. While neutralizing antibody responses were similar in both subjects, during acute infection R880F mounted a broad T cell response, the most dominant components of which targeted epitopes from which escape was limited. In contrast, the primary HIV-specific T cell response in R463F was focused on just two epitopes, one of which rapidly escaped. This comprehensive study highlights both the importance of the contribution of the lower replication capacity of the transmitted/founder virus and an associated induction of a broad primary HIV-specific T cell response, which was not undermined by rapid epitope escape, to long-term viral control in HIV-1 infection. It underscores the importance of the earliest CD8 T cell response targeting regions of the virus proteome that cannot mutate without a high fitness cost, further emphasizing the need for vaccines that elicit a breadth of T cell responses to conserved viral epitopes.

ProGeRF: proteome and genome repeat finder utilizing a fast parallel hash function.

Repetitive element sequences are adjacent, repeating patterns, also called motifs, and can be of different lengths; repetitions can involve their exact or approximate copies. They have been widely used as molecular markers in population biology. Given the sizes of sequenced genomes, various bioinformatics tools have been developed for the extraction of repetitive elements from DNA sequences. However, currently available tools do not provide options for identifying repetitive elements in the genome or proteome, displaying a user-friendly web interface, and performing-exhaustive searches. ProGeRF is a web site for extracting repetitive regions from genome and proteome sequences. It was designed to be efficient, fast, and accurate and primarily user-friendly web tool allowing many ways to view and analyse the results. ProGeRF (Proteome and Genome Repeat Finder) is freely available as a stand-alone program, from which the users can download the source code, and as a web tool. It was developed using the hash table approach to extract perfect and imperfect repetitive regions in a (multi)FASTA file, while allowing a linear time complexity.