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At least 19 recordsLinked to original sources
PubMed2026

Combining Annotation Software to Identify Orthologous Genes (CASIO) Provides a New Dataset of Orthologous Genes for Swallowtail Butterflies.

With the massive increase in genomic resources, it is becoming increasingly popular to analyse thousands of loci across many species. However, many of the available genomes are not annotated, which hinders an efficient search for orthologous protein-coding genes. Here, we aim to develop a semi-automated pipeline and compare four genomic annotation methods (BRAKER2, BUSCO, Miniprot and Scipio). Our results highlight the importance of integrating multiple annotation tools to optimise ortholog detection and improve genomic studies. Each annotation method showed different strengths. BRAKER2 annotated a substantial number of genes. BUSCO, despite limitations inherent to its reference database, identified a higher number of orthologs. Miniprot exhibited notable flexibility in accommodating diverse protein datasets, whereas Scipio successfully recovered a considerable set of genes that were not detected by the other tools. The combination of these tools allowed for more comprehensive ortholog detection. Taking advantage of this pipeline, we developed a comprehensive dataset of orthologous genes for swallowtail butterflies (Lepidoptera: Papilionidae), called Papilionidae_odb, which will facilitate future studies, especially for a non-model group with abundant genomic data and few transcriptomic resources. We tested Papilionidae_odb by inferring a robust phylogenetic framework for Leptocircini using 142 complete genomes, which improved branch support for some phylogenetic relationships, although challenges remained in resolving relationships within certain species groups, likely due to rapid radiations. Our results highlight the complementary nature of the annotation methods and suggest that combining these tools can yield more accurate results in genomic research. This approach was implemented in a Snakemake workflow called CASIO (Combining Annotation Software to Identify Orthologous genes) and can easily be applied to other non-model groups to improve genomic datasets in diverse taxa where transcriptomic resources are still limited.

Animals↗
PubMed2002

Automated ortholog inference from phylogenetic trees and calculation of orthology reliability.

MOTIVATION: Orthologous proteins in different species are likely to have similar biochemical function and biological role. When annotating a newly sequenced genome by sequence homology, the most precise and reliable functional information can thus be derived from orthologs in other species. A standard method of finding orthologs is to compare the sequence tree with the species tree. However, since the topology of phylogenetic tree is not always reliable one might get incorrect assignments. RESULTS: Here we present a novel method that resolves this problem by analyzing a set of bootstrap trees instead of the optimal tree. The frequency of orthology assignments in the bootstrap trees can be interpreted as a support value for the possible orthology of the sequences. Our method is efficient enough to analyze data in the scale of whole genomes. It is implemented in Java and calculates orthology support levels for all pairwise combinations of homologous sequences of two species. The method was tested on simulated datasets and on real data of homologous proteins.

Algorithms↗
PubMed2006

Detecting non-orthology in the COGs database and other approaches grouping orthologs using genome-specific best hits.

Correct orthology assignment is a critical prerequisite of numerous comparative genomics procedures, such as function prediction, construction of phylogenetic species trees and genome rearrangement analysis. We present an algorithm for the detection of non-orthologs that arise by mistake in current orthology classification methods based on genome-specific best hits, such as the COGs database. The algorithm works with pairwise distance estimates, rather than computationally expensive and error-prone tree-building methods. The accuracy of the algorithm is evaluated through verification of the distribution of predicted cases, case-by-case phylogenetic analysis and comparisons with predictions from other projects using independent methods. Our results show that a very significant fraction of the COG groups include non-orthologs: using conservative parameters, the algorithm detects non-orthology in a third of all COG groups. Consequently, sequence analysis sensitive to correct orthology assignments will greatly benefit from these findings.

Algorithms↗
PubMed2005

DoOP: Databases of Orthologous Promoters, collections of clusters of orthologous upstream sequences from chordates and plants.

DoOP (http://doop.abc.hu/) is a database of eukaryotic promoter sequences (upstream regions) aiming to facilitate the recognition of regulatory sites conserved between species. The annotated first exons of human and Arabidopsis thaliana genes were used as queries in BLAST searches to collect the most closely related orthologous first exon sequences from Chordata and Viridiplantae species. Up to 3000 bp DNA segments upstream from these first exons constitute the clusters in the chordate and plant sections of the Database of Orthologous Promoters. Release 1.0 of DoOP contains 21,061 chordate clusters from 284 different species and 7548 plant clusters from 269 different species. The database can be used to find and retrieve promoter sequences of a given gene from various species and it is also suitable to see the most trivial conserved sequence blocks in the orthologous upstream regions. Users can search DoOP with either sequence or text (annotation) to find promoter clusters of various genes. In addition to the sequence data, the positions of the conserved sequence blocks derived from multiple alignments, the positions of repetitive elements and the positions of transcription start sites known from the Eukaryotic Promoter Database (EPD) can be viewed graphically.

Animals↗
PubMed2000

Identification and characterization of mouse orthologs of the AMMECR1 and FACL4 genes deleted in AMME syndrome: orthology of Xq22.3 and MmuXF1-F3.

The contiguous gene deletion syndrome AMME is characterized by Alport syndrome, midface hypoplasia, mental retardation and elliptocytosis and is caused by a deletion in Xq22.3, comprising several genes including COL4A5, FACL4 and AMMECR1. We have now cloned the murine Facl4 and Ammecr1 genes and have mapped both novel murine genes to mouse chromosome X band F1-F3. The murine and human orthologs show 96.5% (FACL4) and 95.2% (AMMECR1) identity at the amino acid level, with conservation of the respective putative subcellular localization signals. Our results show that Facl4 and Ammecr1 are the true murine orthologs of the human genes. Furthermore, the mapping of Facl4 and Ammecr1 to MmuXF1-F3 suggests that this subinterval is orthologous, at least for a portion of Xq22. 3.

Amino Acid Sequence↗
PubMed2003

Molecular analysis of human Siglec-8 orthologs relevant to mouse eosinophils: identification of mouse orthologs of Siglec-5 (mSiglec-F) and Siglec-10 (mSiglec-G).

We recently identified a novel human sialic acid binding immunoglobulin-like lectin, Siglec-8, using mRNA from human eosinophils. To search for a mouse Siglec (mSiglec) ortholog of Siglec-8 and other mouse Siglec paralogs, we conducted public database searches with cDNA sequences of human Siglec-5 to -10 and identified two novel mSiglecs. One has significant sequence identity to human Siglec-5 and is a splice variant of mSiglec-F. The other has greatest sequence identity to human Siglec-10 (mSiglec-G). Both mSiglecs have extracellular Ig-like domains and intracellular tyrosine-based motifs. To determine whether these mSiglecs were relevant to mouse eosinophils, RT-PCR and Northern blot analysis were performed. We detected expression of mSiglec-5 (or -F), -10, and -E mRNA in purified mouse eosinophils, but Northern blot data comparing expression in tissues from normal, IL-5 transgenic, and allergen-sensitized and -challenged mice suggest that mSiglec-10 is probably most relevant to mouse eosinophils.

Amino Acid Sequence↗
PubMed2006

Arabidopsis orthologs of maize chloroplast splicing factors promote splicing of orthologous and species-specific group II introns.

Chloroplast genomes in plants and green algae contain numerous group II introns, large ribozymes that splice via the same chemical steps as spliceosome-mediated splicing in the nucleus. Most chloroplast group II introns are degenerate, requiring interaction with nucleus-encoded proteins to splice in vivo. Genetic approaches in maize (Zea mays) and Chlamydomonas reinhardtii have elucidated distinct sets of proteins that assemble with chloroplast group II introns and facilitate splicing. Little information is available, however, concerning these processes in Arabidopsis (Arabidopsis thaliana). To determine whether the paucity of data concerning chloroplast splicing factors in Arabidopsis reflects a fundamental difference between protein-facilitated group II splicing in monocot and dicot plants, we examined the mutant phenotypes associated with T-DNA insertions in Arabidopsis genes encoding orthologs of the maize chloroplast splicing factors CRS1, CAF1, and CAF2 (AtCRS1, AtCAF1, and AtCAF2). We show that the splicing functions and intron specificities of these proteins are largely conserved between maize and Arabidopsis, indicating that these proteins were recruited to promote the splicing of plastid group II introns prior to the divergence of monocot and dicot plants. We show further that AtCAF1 promotes the splicing of two group II introns, rpoC1 and clpP-intron 1, that are found in Arabidopsis but not in maize; AtCAF1 is the first splicing factor described for these introns. Finally, we show that a strong AtCAF2 allele conditions an embryo-lethal phenotype, adding to the body of data suggesting that cell viability is more sensitive to the loss of plastid translation in Arabidopsis than in maize.

Arabidopsis↗
PubMed2006

Homology modeling of four Y-family, lesion-bypass DNA polymerases: the case that E. coli Pol IV and human Pol kappa are orthologs, and E. coli Pol V and human Pol eta are orthologs.

Y-family DNA polymerases (DNAPs) are a superfamily of evolutionarily related proteins that exist in cells to bypass DNA damage caused by both radiation and chemicals. Cells have multiple Y-family DNAPs, presumably to conduct translesion synthesis (TLS) on DNA lesions of varying structure and conformation. The potent, ubiquitous environmental mutagen/carcinogen benzo[a]pyrene (B[a]P) induces all classes of mutations with G-->T base substitutions predominating. We recently showed that a G-->T mutagenesis pathway for the major adduct of B[a]P ([+ta]-B[a]P-N2-dG) in Escherichia coli depends on Y-family member DNAP V. Since no X-ray crystal study for DNAP V has been reported, no structure is available to help in understanding the structural basis for dATP insertion associated with G-->T mutations from [+ta]-B[a]P-N2-dG. Herein, we do homology modeling to construct a model for UmuC, which is the polymerase subunit of DNAP V. The sequences of eight Y-family DNAPs were aligned based on the positioning of conserved amino acids and an analysis of conserved predicted secondary structure, as well as insights gained from published X-ray structures of five Y-family members. Starting coordinates for UmuC were generated from the backbone coordinates for the Y-family polymerase Dpo4 for reasons discussed, and were refined using molecular dynamics with CHARMM 27. A survey of the literature revealed that E. coli DNAP V and human DNAP eta show a similar pattern of dNTP insertion opposite a variety of DNA lesions. Furthermore, E. coli DNAP IV and human DNAP kappa show a similar dNTP insertional pattern with these same DNA lesions, although the insertional pattern for DNAP IV/kappa differs from the pattern for DNAPs V/eta. These comparisons prompted us to construct and refine models for E. coli DNAP IV and human DNAPs eta and kappa as well. The dNTP/template binding pocket of all four DNAPs was inspected, focusing on the array of seven amino acids that contact the base of the incoming dNTP, as well as the template base. DNAPs V and eta show similarities in this array, and DNAPs IV and kappa also show similarities, although the arrays are different for the two pairs of DNAPs. Thus, there is a correlation between structural similarities and insertional similarities for the pairs DNAPs V/eta and DNAPs IV/kappa. Although the significance of this correlation remains to be elucidated, these observations point the way for future experimental studies.

Amino Acid Sequence↗
PubMed2001

Automatic clustering of orthologs and in-paralogs from pairwise species comparisons.

Orthologs are genes in different species that originate from a single gene in the last common ancestor of these species. Such genes have often retained identical biological roles in the present-day organisms. It is hence important to identify orthologs for transferring functional information between genes in different organisms with a high degree of reliability. For example, orthologs of human proteins are often functionally characterized in model organisms. Unfortunately, orthology analysis between human and e.g. invertebrates is often complex because of large numbers of paralogs within protein families. Paralogs that predate the species split, which we call out-paralogs, can easily be confused with true orthologs. Paralogs that arose after the species split, which we call in-paralogs, however, are bona fide orthologs by definition. Orthologs and in-paralogs are typically detected with phylogenetic methods, but these are slow and difficult to automate. Automatic clustering methods based on two-way best genome-wide matches on the other hand, have so far not separated in-paralogs from out-paralogs effectively. We present a fully automatic method for finding orthologs and in-paralogs from two species. Ortholog clusters are seeded with a two-way best pairwise match, after which an algorithm for adding in-paralogs is applied. The method bypasses multiple alignments and phylogenetic trees, which can be slow and error-prone steps in classical ortholog detection. Still, it robustly detects complex orthologous relationships and assigns confidence values for both orthologs and in-paralogs. The program, called INPARANOID, was tested on all completely sequenced eukaryotic genomes. To assess the quality of INPARANOID results, ortholog clusters were generated from a dataset of worm and mammalian transmembrane proteins, and were compared to clusters derived by manual tree-based ortholog detection methods. This study led to the identification with a high degree of confidence of over a dozen novel worm-mammalian ortholog assignments that were previously undetected because of shortcomings of phylogenetic methods.A WWW server that allows searching for orthologs between human and several fully sequenced genomes is installed at http://www.cgb.ki.se/inparanoid/. This is the first comprehensive resource with orthologs of all fully sequenced eukaryotic genomes. Programs and tables of orthology assignments are available from the same location.

Algorithms↗
PubMed2006

Improving the specificity of high-throughput ortholog prediction.

BACKGROUND: Orthologs (genes that have diverged after a speciation event) tend to have similar function, and so their prediction has become an important component of comparative genomics and genome annotation. The gold standard phylogenetic analysis approach of comparing available organismal phylogeny to gene phylogeny is not easily automated for genome-wide analysis; therefore, ortholog prediction for large genome-scale datasets is typically performed using a reciprocal-best-BLAST-hits (RBH) approach. One problem with RBH is that it will incorrectly predict a paralog as an ortholog when incomplete genome sequences or gene loss is involved. In addition, there is an increasing interest in identifying orthologs most likely to have retained similar function. RESULTS: To address these issues, we present here a high-throughput computational method named Ortholuge that further evaluates previously predicted orthologs (including those predicted using an RBH-based approach) - identifying which orthologs most closely reflect species divergence and may more likely have similar function. Ortholuge analyzes phylogenetic distance ratios involving two comparison species and an outgroup species, noting cases where relative gene divergence is atypical. It also identifies some cases of gene duplication after species divergence. Through simulations of incomplete genome data/gene loss, we show that the vast majority of genes falsely predicted as orthologs by an RBH-based method can be identified. Ortholuge was then used to estimate the number of false-positives (predominantly paralogs) in selected RBH-predicted ortholog datasets, identifying approximately 10% paralogs in a eukaryotic data set (mouse-rat comparison) and 5% in a bacterial data set (Pseudomonas putida - Pseudomonas syringae species comparison). Higher quality (more precise) datasets of orthologs, which we term "ssd-orthologs" (supporting-species-divergence-orthologs), were also constructed. These datasets, as well as Ortholuge software that may be used to characterize other species' datasets, are available at http://www.pathogenomics.ca/ortholuge/ (software under GNU General Public License). CONCLUSION: The Ortholuge method reported here appears to significantly improve the specificity (precision) of high-throughput ortholog prediction for both bacterial and eukaryotic species. This method, and its associated software, will aid those performing various comparative genomics-based analyses, such as the prediction of conserved regulatory elements upstream of orthologous genes.

Algorithms↗
PubMed2003

Comprehensive analysis of orthologous protein domains using the HOPS database.

One of the most reliable methods for protein function annotation is to transfer experimentally known functions from orthologous proteins in other organisms. Most methods for identifying orthologs operate on a subset of organisms with a completely sequenced genome, and treat proteins as single-domain units. However, it is well known that proteins are often made up of several independent domains, and there is a wealth of protein sequences from genomes that are not completely sequenced. A comprehensive set of protein domain families is found in the Pfam database. We wanted to apply orthology detection to Pfam families, but first some issues needed to be addressed. First, orthology detection becomes impractical and unreliable when too many species are included. Second, shorter domains contain less information. It is therefore important to assess the quality of the orthology assignment and avoid very short domains altogether. We present a database of orthologous protein domains in Pfam called HOPS: Hierarchical grouping of Orthologous and Paralogous Sequences. Orthology is inferred in a hierarchic system of phylogenetic subgroups using ortholog bootstrapping. To avoid the frequent errors stemming from horizontally transferred genes in bacteria, the analysis is presently limited to eukaryotic genes. The results are accessible in the graphical browser NIFAS, a Java tool originally developed for analyzing phylogenetic relations within Pfam families. The method was tested on a set of curated orthologs with experimentally verified function. In comparison to tree reconciliation with a complete species tree, our approach finds significantly more orthologs in the test set. Examples for investigating gene fusions and domain recombination using HOPS are given.

Animals↗
PubMed2006

Benchmarking ortholog identification methods using functional genomics data.

BACKGROUND: The transfer of functional annotations from model organism proteins to human proteins is one of the main applications of comparative genomics. Various methods are used to analyze cross-species orthologous relationships according to an operational definition of orthology. Often the definition of orthology is incorrectly interpreted as a prediction of proteins that are functionally equivalent across species, while in fact it only defines the existence of a common ancestor for a gene in different species. However, it has been demonstrated that orthologs often reveal significant functional similarity. Therefore, the quality of the orthology prediction is an important factor in the transfer of functional annotations (and other related information). To identify protein pairs with the highest possible functional similarity, it is important to qualify ortholog identification methods. RESULTS: To measure the similarity in function of proteins from different species we used functional genomics data, such as expression data and protein interaction data. We tested several of the most popular ortholog identification methods. In general, we observed a sensitivity/selectivity trade-off: the functional similarity scores per orthologous pair of sequences become higher when the number of proteins included in the ortholog groups decreases. CONCLUSION: By combining the sensitivity and the selectivity into an overall score, we show that the InParanoid program is the best ortholog identification method in terms of identifying functionally equivalent proteins.

Algorithms↗
PubMed2004

Using shared genomic synteny and shared protein functions to enhance the identification of orthologous gene pairs.

MOTIVATION: The identification of orthologous gene pairs is generally based on sequence similarity. Gene pairs that are mutually 'best hits' between the genomes being compared are asserted to be orthologs. Although this method identifies most orthologous gene pairs with high confidence, it will miss a fraction of them, especially genes in duplicated gene families. In addition, the approach depends heavily on the completeness and quality of gene annotation. When the gene sequences are not correctly represented the approach is unlikely to find the correct ortholog. To overcome these limitations, we have developed an approach to identify orthologous gene pairs using shared chromosomal synteny and the annotation of protein function. RESULTS: Assembled mouse and human genomes were used to identify the regions of conserved synteny between these genomes. 'Syntenic anchors' are conserved non-repetitive locations between mouse and human genomes. Using these anchors, we identified blocks of sequences that contain consistently ordered anchors between the two genomes (syntenic blocks). The synteny information has been used to help us identify orthologous gene pairs between mouse and human genomes. The approach combines the mutual selection of the best tBlastX hits between human and mouse transcripts, and inferring gene orthologous relationships based on sharing syntenic anchors, collocating in the same syntenic blocks and sharing the same annotated protein function. Using this approach, we were able to find 19,357 orthologous gene pairs between human and mouse genomes, a 20% increase in the number of orthologs identified by conventional approaches.

Algorithms↗
PubMed2006

Automatic clustering of orthologs and inparalogs shared by multiple proteomes.

MOTIVATION: The complete sequencing of many genomes has made it possible to identify orthologous genes descending from a common ancestor. However, reconstruction of evolutionary history over long time periods faces many challenges due to gene duplications and losses. Identification of orthologous groups shared by multiple proteomes therefore becomes a clustering problem in which an optimal compromise between conflicting evidences needs to be found. RESULTS: Here we present a new proteome-scale analysis program called MultiParanoid that can automatically find orthology relationships between proteins in multiple proteomes. The software is an extension of the InParanoid program that identifies orthologs and inparalogs in pairwise proteome comparisons. MultiParanoid applies a clustering algorithm to merge multiple pairwise ortholog groups from InParanoid into multi-species ortholog groups. To avoid outparalogs in the same cluster, MultiParanoid only combines species that share the same last ancestor. To validate the clustering technique, we compared the results to a reference set obtained by manual phylogenetic analysis. We further compared the results to ortholog groups in KOGs and OrthoMCL, which revealed that MultiParanoid produces substantially fewer outparalogs than these resources. AVAILABILITY: MultiParanoid is a freely available standalone program that enables efficient orthology analysis much needed in the post-genomic era. A web-based service providing access to the original datasets, the resulting groups of orthologs, and the source code of the program can be found at http://multiparanoid.cgb.ki.se.

Algorithms↗
PubMed2005

NEP1 orthologs encoding necrosis and ethylene inducing proteins exist as a multigene family in Phytophthora megakarya, causal agent of black pod disease on cacao.

Phvytophthora megakarya is a devastating oomycete pathogen that causes black pod disease in cacao. Phytophthora species produce a protein that has a similar sequence to the necrosis and ethylene inducing protein (Nep1) of Fusarium oxysporum. Multiple copies of NEP1 orthologs (PmegNEP) have been identified in P. megakarya and four other Phytophthora species (P. citrophthora, P. capsici, P. palmivora, and P. sojae). Genome database searches confirmed the existence of multiple copies of NEP1 orthologs in P. sojae and P. ramorum. In this study, nine different PmegNEP orthologs from P. megakarya strain Mk-1 were identified and analyzed. Of these nine orthologs, six were expressed in mycelium and in P. megakarya zoospore-infected cacao leaf tissue. The remaining two clones are either regulated differently, or are nonfunctional genes. Sequence analysis revealed that six PmegNEP orthologs were organized in two clusters of three orthologs each in the P. megakarya genome. Evidence is presented for the instability in the P. megakarya genome resulting from duplications, inversions, and fused genes resulting in multiple NEP1 orthologs. Traits characteristic of the Phytophthora genome, such as the clustering of NEP1 orthologs, the lack of CATT and TATA boxes, the lack of introns, and the short distance between ORFs were also observed.

Amino Acid Sequence↗
PubMed2001

Intrinsic versus extrinsic stabilization of enzymes: the interaction of solutes and temperature on A4-lactate dehydrogenase orthologs from warm-adapted and cold-adapted marine fishes.

We examined the effects of temperature and stabilizing solutes on A4-lactate dehydrogenase (A4-LDH) from warm- and cold-adapted fishes, to determine how extrinsic stabilizers affect orthologs with different intrinsic stabilities. Conformational changes during substrate binding are rate-limiting for A4-LDH, thus stabilization due to intrinsic or extrinsic factors leads to decreased activity. A4-LDH from a warm-temperate goby (Gillichthys mirabilis), which has lower values for kcat and the Michaelis constant for pyruvate ( K m PYR), was intrinsically more stable than the orthologs of the cold-adapted Antarctic notothenioids Parachaenichthys charcoti and Chionodraco rastrospinosus, as shown by a higher apparent transition ('melting') temperature (Tm(APP)). We used four solutes, glycerol, sucrose, trimethylamine-N-oxide and poly(ethylene glycol) 8000, which stabilize proteins through different modes of preferential exclusion, to study temperature-solute interactions of the three orthologs. Changes in Tm(APP) were similar for all orthologs in each solute tested, but the catalytic rate of G. mirabilis A4-LDH was decreased most by solutes and increased most by temperature. In contrast, the K m PYR values of the Antarctic orthologs were more affected than that of the goby by both solutes and temperature. We conclude that (a) preferential exclusion of solutes functions within the native state of A4-LDH to favor conformational microstates with minimal surface area; (b) the varied effects of the different solutes on the kinetic properties are due to the interaction between this nonspecific stabilization and the differing intrinsic stabilities of the orthologs; (c) the catalytic rates of A4-LDH orthologs are equally affected by stabilizing solutes, if measurements are made at physiologically appropriate temperatures; and (d) global stability and localized flexibility of these A4-LDH orthologs may evolve independently.

Animals↗
PubMed2001

Comprehensive comparison between locations of orthologous genes on archaeal and bacterial genomes.

MOTIVATION: Following an extensive search for orthologous genes between the complete genomes from archaea and bacteria, the spatial association of the orthologs has been investigated in terms of synteny, the conservation of the order of neighboring genes. However, the relationships between the relative locations of remote orthologs over entire genomes have not been shown. RESULTS: Comprehensive comparisons between the locations of orthologs on nineteen archaeal and bacterial genomes are presented by the location to location correspondence based on the gene-location distance. When the two genomes are rotated such that a pair of orthologs with the shortest distance is set in the same angle, a statistically significant number of orthologs maintain their relative locations between the genomes. Even by the short distances at the 5% significance level, the rotations are restricted within a narrow range, suggesting an intrinsic angle for realizing similar locations between the orthologs in each genome pair. Furthermore, the rotations in the restricted range agree with the replication origin and terminus sites for the analyzed genomes where such sites are known. The relationship between location-maintained orthologs and gene function is also discussed.

Chromosome Mapping↗
PubMed2006

OrthologID: automation of genome-scale ortholog identification within a parsimony framework.

MOTIVATION: The determination of gene orthology is a prerequisite for mining and utilizing the rapidly increasing amount of sequence data for genome-scale phylogenetics and comparative genomic studies. Until now, most researchers use pairwise distance comparisons algorithms, such as BLAST, COG, RBH, RSD and INPARANOID, to determine gene orthology. In contrast, orthology determination within a character-based phylogenetic framework has not been utilized on a genomic scale owing to the lack of efficiency and automation. RESULTS: We have developed OrthologID, a Web application that automates the labor-intensive procedures of gene orthology determination within a character-based phylogenetic framework, thus making character-based orthology determination on a genomic scale possible. In addition to generating gene family trees and determining orthologous gene sets for complete genomes, OrthologID can also identify diagnostic characters that define each orthologous gene set, as well as diagnostic characters that are responsible for classifying query sequences from other genomes into specific orthology groups. The OrthologID database currently includes several complete plant genomes, including Arabidopsis thaliana, Oryza sativa, Populus trichocarpa, as well as a unicellular outgroup, Chlamydomonas reinhardtii. To improve the general utility of OrthologID beyond plant species, we plan to expand our sequence database to include the fully sequenced genomes of prokaryotes and other non-plant eukaryotes. AVAILABILITY: http://nypg.bio.nyu.edu/orthologid/

Algorithms↗