A Quadruple Revolution: Deciphering Biological Complexity with Artificial Intelligence, Multiomics, Precision Medicine, and Planetary Health.

A quiet quadruple revolution has been in the making in systems science with convergence of (1) artificial intelligence, machine learning, and other digital technologies; (2) multiomics big data integration; (3) growing interest in the "variability science" of precision/personalized medicine that aims to account for patient-to-patient and between-population differences in disease susceptibilities and responses to health interventions such as drugs, nutrition, vaccines, and radiation; and (4) planetary health scholarship that both scales up and integrates biological, clinical, and ecological contexts of health and disease. Against this overarching background, this article presents and highlights some of the salient challenges and prospects of multiomics research, emphasizing the attendant pivotal role of systems medicine and systems biology. In addition, we emphasize the rapidly growing importance of planetary health research for systems medicine, particularly amid climate emergency, ecological degradation, and loss of planetary biodiversity. Looking ahead, we anticipate that the integration and utilization of multiomics big data and artificial intelligence will drive further progress in systems medicine and systems biology, heralding a promising future for both human and planetary health.

Inference of selective forces on house mouse genomes during secondary contact in East Asia.

The house mouse (Mus musculus), which is commensal to humans, has spread globally via human activities, leading to secondary contact between genetically divergent subspecies. This pattern of genetic admixture can provide insights into the selective forces at play in this well-studied model organism. Our analysis of 163 house mouse genomes, with a particular focus on East Asia, revealed substantial admixture between the subspecies castaneus and musculus, particularly in Japan and southern China. We revealed, despite the different level of autosomal admixture among regions, that all Y Chromosomes in the East Asian samples belonged to the musculus-type haplogroup, potentially explained by genomic conflict under sex-ratio distortion owing to varying copy numbers of ampliconic genes on sex chromosomes, Slx and Sly Our computer simulations, designed to replicate the observed scenario, show that the preferential fixation of musculus-type Y Chromosomes can be achieved with a slight increase in the male-to-female birth ratio. We also investigated the influence of selection on the posthybridization of the subspecies castaneus and musculus in Japan. Even though the genetic background of most Japanese samples closely resembles the subspecies musculus, certain genomic regions overrepresented the castaneus-like genetic components, particularly in immune-related genes. Furthermore, a large genomic block (∼2 Mbp) containing a vomeronasal/olfactory receptor gene cluster predominantly harbored castaneus-type haplotypes in the Japanese samples, highlighting the crucial role of olfaction-based recognition in shaping hybrid genomes.

Current trends in RNA virus detection through metatranscriptome sequencing data.

With advances in sequencing technology, metatranscriptome sequencing from a variety of environmental and biological sources has revealed the existence of various previously unknown RNA viruses. This review presents recent major RNA virome studies sampled from invertebrate and vertebrate species as well as aquatic environments. In particular, we focus on severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and related RNA virus identification through metatranscriptome sequencing analyses. Recently developed bioinformatics software and databases for RNA virus identification are introduced. A relationship between newly identified RNA viruses and endogenous viral elements in host genomes is also discussed.

A New Approach to Drug Repurposing with Two-Stage Prediction, Machine Learning, and Unsupervised Clustering of Gene Expression.

Drug repurposing has broad importance in planetary health for therapeutics innovation in infectious diseases as well as common or rare chronic human diseases. Drug repurposing has also proved important to develop interventions against the COVID-19 pandemic. We propose a new approach for drug repurposing involving two-stage prediction and machine learning. First, diseases are clustered by gene expression on the premise that similar patterns of altered gene expression imply critical pathways shared in different disease conditions. Next, drug efficacy is assessed by the reversibility of abnormal gene expression, and results are clustered to identify repurposing targets. To cluster similar diseases, gene expression data from 262 cases of 31 diseases and 268 controls were analyzed by Uniform Manifold Approximation and Projection for Dimension Reduction followed by k-means to optimize the number of clusters. For evaluation, we examined disease-specific gene expression data for inclusion, body myositis, polymyositis, and dermatomyositis (DM), and used LINCS L1000 characteristic direction signatures search engine (L1000CDS2) to obtain lists of small-molecule compounds that reversed the expression patterns of these specifically altered genes as candidates for drug repurposing. Finally, the functions of affected genes were analyzed by Gene Set Enrichment Analysis to examine consistency with expected drug efficacy. Consequently, we found disease-specific gene expression, and importantly, identified 20 drugs such as BMS-387032, phorbol-12-myristate-13-acetate, mitoxantrone, alvocidib, and vorinostat as candidates for repurposing. These were previously noted to be effective against two of the three diseases, and have a high probability of being effective against the other. That is, inclusion body myositis and DM. The two-stage prediction approach to drug repurposing presented here offers innovation to inform future drug discovery and clinical trials in a variety of human diseases.

Multi-Omics and Artificial Intelligence-Guided Drug Repositioning: Prospects, Challenges, and Lessons Learned from COVID-19.

Drug repurposing is of interest for therapeutics innovation in many human diseases including coronavirus disease 2019 (COVID-19). Methodological innovations in drug repurposing are currently being empowered by convergence of omics systems science and digital transformation of life sciences. This expert review article offers a systematic summary of the application of artificial intelligence (AI), particularly machine learning (ML), to drug repurposing and classifies and introduces the common clustering, dimensionality reduction, and other methods. We highlight, as a present-day high-profile example, the involvement of AI/ML-based drug discovery in the COVID-19 pandemic and discuss the collection and sharing of diverse data types, and the possible futures awaiting drug repurposing in an era of AI/ML and digital technologies. The article provides new insights on convergence of multi-omics and AI-based drug repurposing. We conclude with reflections on the various pathways to expedite innovation in drug development through drug repurposing for prompt responses to the current COVID-19 pandemic and future ecological crises in the 21st century.

Whole-Genome Sequencing of Vero E6 (VERO C1008) and Comparative Analysis of Four Vero Cell Sublines.

The Vero cell line is an immortalized cell line established from kidney epithelial cells of the African green monkey. A variety of Vero sublines have been developed and can be classified into four major cell lineages. In this study, we determined the whole-genome sequence of Vero E6 (VERO C1008), which is one of the most widely used cell lines for the proliferation and isolation of severe acute respiratory syndrome coronaviruses (SARS-CoVs), and performed comparative analysis among Vero JCRB0111, Vero CCL-81, Vero 76, and Vero E6. Analysis of the copy number changes and loss of heterozygosity revealed that these four sublines share a large deletion and loss of heterozygosity on chromosome 12, which harbors type I interferon and CDKN2 gene clusters. We identified a substantial number of genetic differences among the sublines including single nucleotide variants, indels, and copy number variations. The spectrum of single nucleotide variants indicated a close genetic relationship between Vero JCRB0111 and Vero CCL-81, and between Vero 76 and Vero E6, and a considerable genetic gap between the former two and the latter two lines. In contrast, we confirmed the pattern of genomic integration sites of simian endogenous retroviral sequences, which was consistent among the sublines. We identified subline-specific/enriched loss of function and missense variants, which potentially contribute to the differences in response to viral infection among the Vero sublines. In particular, we identified four genes (IL1RAP, TRIM25, RB1CC1, and ATG2A) that contained missense variants specific or enriched in Vero E6. In addition, we found that V739I variants of ACE2, which functions as the receptor for SARS-CoVs, were heterozygous in Vero JCRB0111, Vero CCL-81, and Vero 76; however, Vero E6 harbored only the allele with isoleucine, resulting from the loss of one of the X chromosomes.

Identification of Characteristic Genomic Markers in Human Hepatoma HuH-7 and Huh7.5.1-8 Cell Lines.

The human hepatoma-derived HuH-7 cell line and its derivatives (Huh7.5 and Huh7.5.1) have been widely used as a convenient experimental substitute for primary hepatocytes. In particular, these cell lines represent host cells suitable for propagating the hepatitis C virus (HCV) in vitro. The Huh7.5.1-8 cell line, a subline of Huh7.5.1, can propagate HCV more efficiently than its parental cells. To provide genomic information for cells' quality control, we performed whole-genome sequencing of HuH-7 and Huh7.5.1-8 and identified their characteristic genomic deletions, some of which are applicable to an in-house test for cell authentication. Among the genes related to HCV infection and replication, 53 genes were found to carry missense or loss-of-function mutations likely specific to the HuH-7 and/or Huh7.5.1-8. Eight genes, including DDX58 (RIG-I), BAX, EP300, and SPP1 (osteopontin), contained mutations observed only in Huh7.5.1-8 or mutations with higher frequency in Huh7.5.1-8. These mutations might be relevant to phenotypic differences between the two cell lines and may also serve as genetic markers to distinguish Huh7.5.1-8 cells from the ancestral HuH-7 cells.

Exhaustive identification of conserved upstream open reading frames with potential translational regulatory functions from animal genomes.

Upstream open reading frames (uORFs) are present in the 5'-untranslated regions of many eukaryotic mRNAs, and some peptides encoded by these regions play important regulatory roles in controlling main ORF (mORF) translation. We previously developed a novel pipeline, ESUCA, to comprehensively identify plant uORFs encoding functional peptides, based on genome-wide identification of uORFs with conserved peptide sequences (CPuORFs). Here, we applied ESUCA to diverse animal genomes, because animal CPuORFs have been identified only by comparing uORF sequences between a limited number of species, and how many previously identified CPuORFs encode regulatory peptides is unclear. By using ESUCA, 1517 (1373 novel and 144 known) CPuORFs were extracted from four evolutionarily divergent animal genomes. We examined the effects of 17 human CPuORFs on mORF translation using transient expression assays. Through these analyses, we identified seven novel regulatory CPuORFs that repressed mORF translation in a sequence-dependent manner, including one conserved only among Eutheria. We discovered a much higher number of animal CPuORFs than previously identified. Since most human CPuORFs identified in this study are conserved across a wide range of Eutheria or a wider taxonomic range, many CPuORFs encoding regulatory peptides are expected to be found in the identified CPuORFs.

Comprehensive genome-wide identification of angiosperm upstream ORFs with peptide sequences conserved in various taxonomic ranges using a novel pipeline, ESUCA.

BACKGROUND: Upstream open reading frames (uORFs) in the 5'-untranslated regions (5'-UTRs) of certain eukaryotic mRNAs encode evolutionarily conserved functional peptides, such as cis-acting regulatory peptides that control translation of downstream main ORFs (mORFs). For genome-wide searches for uORFs with conserved peptide sequences (CPuORFs), comparative genomic studies have been conducted, in which uORF sequences were compared between selected species. To increase chances of identifying CPuORFs, we previously developed an approach in which uORF sequences were compared using BLAST between Arabidopsis and any other plant species with available transcript sequence databases. If this approach is applied to multiple plant species belonging to phylogenetically distant clades, it is expected to further comprehensively identify CPuORFs conserved in various plant lineages, including those conserved among relatively small taxonomic groups. RESULTS: To efficiently compare uORF sequences among many species and efficiently identify CPuORFs conserved in various taxonomic lineages, we developed a novel pipeline, ESUCA. We applied ESUCA to the genomes of five angiosperm species, which belong to phylogenetically distant clades, and selected CPuORFs conserved among at least three different orders. Through these analyses, we identified 89 novel CPuORF families. As expected, ESUCA analysis of each of the five angiosperm genomes identified many CPuORFs that were not identified from ESUCA analyses of the other four species. However, unexpectedly, these CPuORFs include those conserved across wide taxonomic ranges, indicating that the approach used here is useful not only for comprehensive identification of narrowly conserved CPuORFs but also for that of widely conserved CPuORFs. Examination of the effects of 11 selected CPuORFs on mORF translation revealed that CPuORFs conserved only in relatively narrow taxonomic ranges can have sequence-dependent regulatory effects, suggesting that most of the identified CPuORFs are conserved because of functional constraints of their encoded peptides. CONCLUSIONS: This study demonstrates that ESUCA is capable of efficiently identifying CPuORFs likely to be conserved because of the functional importance of their encoded peptides. Furthermore, our data show that the approach in which uORF sequences from multiple species are compared with those of many other species, using ESUCA, is highly effective in comprehensively identifying CPuORFs conserved in various taxonomic ranges.

Computational Drug-repositioning Approach Identifying Sirolimus as a Potential Therapeutic Option for Inflammatory Dilated Cardiomyopathy.

OBJECTIVE: The aim of this study was to determine promising treatment options for human inflammatory dilated cardiomyopathy using a computational drug-repositioning approach (repurposing established drug compounds for new therapeutic indications). BACKGROUND: If the myocardial tissue is detected to be infiltrated with inflammatory cells, primarily of lymphocytes, and if the virus is confirmed using genetic examination (PCR) or immunostaining, the infection is suspected. However, there is no specific treatment (i. e., an antiviral drug) even if the virus is identified; therefore, we used Connectivity Map to identify compounds showing inverse drug-disease signatures, indicating activity against inflammatory dilated cardiomyopathy. RESULTS: Potential drug-repositioning candidates for the treatment of inflammatory dilated cardiomyopathy were explored through a systematic comparison of the gene expression profiles induced by drugs using Gene Expression Omnibus and Connectivity Map databases. CONCLUSION: Using a computational drug-repositioning approach based on the integration of publicly available gene expression signatures of drugs and diseases, sirolimus was suggested as a novel therapeutic option for inflammatory dilated cardiomyopathy.

Comprehensive phylogenomic analysis reveals a novel cluster of simian endogenous retroviral sequences in Colobinae monkeys.

Simian retrovirus (SRV) is a type-D betaretrovirus infectious to the Old World monkeys causing a variety of symptoms. SRVs are also present in the Old World monkey genomes as endogenous forms, which are referred to as Simian endogenous retroviruses (SERVs). Although many SERV sequences have been identified in Cercopithecinae genomes, with potential of encoding all functional genes, the distribution of SERVs in genomes and evolutionary relationship between exogeneous SRVs and SERVs remains unclear. In this study, we comprehensively investigated seven draft genome sequences of the Old World monkeys, and identified a novel cluster of SERVs in the two Rhinopithecus (R. roxellana and R. bieti) genomes, which belong to the Colobinae subfamily. The Rhinopithecus genomes harbored higher copy numbers of SERVs than the Cercopithecinae genomes. A reconstructed phylogenetic tree showed that the Colobinae SERVs formed a distinct cluster from SRVs and Cercopithecinae SERVs, and more closely related to exogenous SRVs than Cercopithecinae SERVs. Three radical amino acid substitutions specific to Cercopithecinae SERVs, which potentially affect the infectious ability of SERVs, were also identified in the proviral envelope protein. In addition, we found many integration events of SERVs were genus- or species-specific, suggesting the recent activity of SERVs in the Old World monkey genomes. The results suggest that SERVs in Cercopithecinae and Colobinae monkeys were endogenized after the divergence of subfamilies and do not transmit across subfamilies. Our findings also support the hypothesis that Colobinae SERVs are direct ancestors of SRV-6, which has a different origin from the other exogenous SRVs. These findings shed novel insight into the evolutionary history of SERVs, and may help to understand the process of endogenization of SRVs.

A Generalized Linear Model for Decomposing Cis-regulatory, Parent-of-Origin, and Maternal Effects on Allele-Specific Gene Expression.

Joint quantification of genetic and epigenetic effects on gene expression is important for understanding the establishment of complex gene regulation systems in living organisms. In particular, genomic imprinting and maternal effects play important roles in the developmental process of mammals and flowering plants. However, the influence of these effects on gene expression are difficult to quantify because they act simultaneously with cis-regulatory mutations. Here we propose a simple method to decompose cis-regulatory (i.e., allelic genotype), genomic imprinting [i.e., parent-of-origin (PO)], and maternal [i.e., maternal genotype (MG)] effects on allele-specific gene expression using RNA-seq data obtained from reciprocal crosses. We evaluated the efficiency of method using a simulated dataset and applied the method to whole-body Drosophila and mouse trophoblast stem cell (TSC) and liver RNA-seq data. Consistent with previous studies, we found little evidence of PO and MG effects in adult Drosophila samples. In contrast, we identified dozens and hundreds of mouse genes with significant PO and MG effects, respectively. Interestingly, a similar number of genes with significant PO effect were detect in mouse TSCs and livers, whereas more genes with significant MG effect were observed in livers. Further application of this method will clarify how these three effects influence gene expression levels in different tissues and developmental stages, and provide novel insight into the evolution of gene expression regulation.

Sustained heterozygosity across a self-incompatibility locus in an inbred ascidian.

Because self-incompatibility loci are maintained heterozygous and recombination within self-incompatibility loci would be disadvantageous, self-incompatibility loci are thought to contribute to structural and functional differentiation of chromosomes. Although the hermaphrodite chordate, Ciona intestinalis, has two self-incompatibility genes, this incompatibility system is incomplete and self-fertilization occurs under laboratory conditions. Here, we established an inbred strain of C. intestinalis by repeated self-fertilization. Decoding genome sequences of sibling animals of this strain identified a 2.4-Mbheterozygous region on chromosome 7. A self-incompatibility gene, Themis-B, was encoded within this region. This observation implied that this self-incompatibility locus and the linkage disequilibrium of its flanking region contribute to the formation of the 2.4-Mb heterozygous region, probably through recombination suppression. We showed that different individuals in natural populations had different numbers and different combinations of Themis-B variants, and that the rate of self-fertilization varied among these animals. Our result explains why self-fertilization occurs under laboratory conditions. It also supports the concept that the Themis-B locus is preferentially retained heterozygous in the inbred line and contributes to the formation of the 2.4-Mb heterozygous region. High structural variations might suppress recombination, and this long heterozygous region might represent a preliminary stage of structural differentiation of chromosomes.

Guidelines for the nomenclature of genetic elements in tunicate genomes.

Tunicates are invertebrate members of the chordate phylum, and are considered to be the sister group of vertebrates. Tunicates are composed of ascidians, thaliaceans, and appendicularians. With the advent of inexpensive high-throughput sequencing, the number of sequenced tunicate genomes is expected to rise sharply within the coming years. To facilitate comparative genomics within the tunicates, and between tunicates and vertebrates, standardized rules for the nomenclature of tunicate genetic elements need to be established. Here we propose a set of nomenclature rules, consensual within the community, for predicted genes, pseudogenes, transcripts, operons, transcriptional cis-regulatory regions, transposable elements, and transgenic constructs. In addition, the document proposes guidelines for naming transgenic and mutant lines.

Exploring functionally related enzymes using radially distributed properties of active sites around the reacting points of bound ligands.

BACKGROUND: Structural genomics approaches, particularly those solving the 3D structures of many proteins with unknown functions, have increased the desire for structure-based function predictions. However, prediction of enzyme function is difficult because one member of a superfamily may catalyze a different reaction than other members, whereas members of different superfamilies can catalyze the same reaction. In addition, conformational changes, mutations or the absence of a particular catalytic residue can prevent inference of the mechanism by which catalytic residues stabilize and promote the elementary reaction. A major hurdle for alignment-based methods for prediction of function is the absence (despite its importance) of a measure of similarity of the physicochemical properties of catalytic sites. To solve this problem, the physicochemical features radially distributed around catalytic sites should be considered in addition to structural and sequence similarities. RESULTS: We showed that radial distribution functions (RDFs), which are associated with the local structural and physicochemical properties of catalytic active sites, are capable of clustering oxidoreductases and transferases by function. The catalytic sites of these enzymes were also characterized using the RDFs. The RDFs provided a measure of the similarity among the catalytic sites, detecting conformational changes caused by mutation of catalytic residues. Furthermore, the RDFs reinforced the classification of enzyme functions based on conventional sequence and structural alignments. CONCLUSIONS: Our results demonstrate that the application of RDFs provides advantages in the functional classification of enzymes by providing information about catalytic sites.

Proteomic profiling reveals compartment-specific, novel functions of ascidian sperm proteins.

In this study, we performed extensive proteomic analysis of sperm from the ascidian Ciona intestinalis. Sperm were fractionated into heads and flagella, followed by further separation into Triton X-100-soluble and -insoluble fractions. Proteins from each fraction and whole sperm were separated by isoelectric focusing using two different pH ranges, followed by SDS-PAGE at two different polyacrylamide concentrations. In total, 1,294 protein spots representing 304 non-redundant proteins were identified by mass spectrometry (MALDI-TOF). On comparison of the proteins in each fraction, we were able to identify the proteins specific to different sperm compartments. Further comparison with the testis proteome allowed the pairing of proteins with sperm-specific functions. Together with information on gene expression in developing embryos and adult tissues, these results provide insight into novel cellular and functional aspects of sperm proteins, such as distinct localization of actin isoforms, novel Ca(2+)-binding proteins in axonemes, localization of testis-specific serine/threonine kinase, and the presence of G-protein coupled signaling and ubiquitin pathway in sperm flagella.

Predicted expansion of the claudin multigene family.

Claudins (Cldn) are essential membrane proteins of tight junctions (TJs), which form the paracellular permselective barrier. They are produced by a multi-gene family of 24 reported members in mouse and human. Based on a comprehensive search combined with phylogenetic analyses, we identified three novel claudins (claudin-25, -26, and -27). Quantitative RT-PCR revealed that the three novel claudins were expressed in a tissue- and/or developmental stage-dependent manner. Claudins-25 and -26, but not claudin-27, were immunofluorescently localized to TJs when exogenously expressed in cultured MDCK and Eph epithelial cell lines. These findings expand the claudin family to include at least 27 members.

CIPRO 2.5: Ciona intestinalis protein database, a unique integrated repository of large-scale omics data, bioinformatic analyses and curated annotation, with user rating and reviewing functionality.

The Ciona intestinalis protein database (CIPRO) is an integrated protein database for the tunicate species C. intestinalis. The database is unique in two respects: first, because of its phylogenetic position, Ciona is suitable model for understanding vertebrate evolution; and second, the database includes original large-scale transcriptomic and proteomic data. Ciona intestinalis has also been a favorite of developmental biologists. Therefore, large amounts of data exist on its development and morphology, along with a recent genome sequence and gene expression data. The CIPRO database is aimed at collecting those published data as well as providing unique information from unpublished experimental data, such as 3D expression profiling, 2D-PAGE and mass spectrometry-based large-scale analyses at various developmental stages, curated annotation data and various bioinformatic data, to facilitate research in diverse areas, including developmental, comparative and evolutionary biology. For medical and evolutionary research, homologs in humans and major model organisms are intentionally included. The current database is based on a recently developed KH model containing 36,034 unique sequences, but for higher usability it covers 89,683 all known and predicted proteins from all gene models for this species. Of these sequences, more than 10,000 proteins have been manually annotated. Furthermore, to establish a community-supported protein database, these annotations are open to evaluation by users through the CIPRO website. CIPRO 2.5 is freely accessible at http://cipro.ibio.jp/2.5.

Improved genome assembly and evidence-based global gene model set for the chordate Ciona intestinalis: new insight into intron and operon populations.

BACKGROUND: The draft genome sequence of the ascidian Ciona intestinalis, along with associated gene models, has been a valuable research resource. However, recently accumulated expressed sequence tag (EST)/cDNA data have revealed numerous inconsistencies with the gene models due in part to intrinsic limitations in gene prediction programs and in part to the fragmented nature of the assembly. RESULTS: We have prepared a less-fragmented assembly on the basis of scaffold-joining guided by paired-end EST and bacterial artificial chromosome (BAC) sequences, and BAC chromosomal in situ hybridization data. The new assembly (115.2 Mb) is similar in length to the initial assembly (116.7 Mb) but contains 1,272 (approximately 50%) fewer scaffolds. The largest scaffold in the new assembly incorporates 95 initial-assembly scaffolds. In conjunction with the new assembly, we have prepared a greatly improved global gene model set strictly correlated with the extensive currently available EST data. The total gene number (15,254) is similar to that of the initial set (15,582), but the new set includes 3,330 models at genomic sites where none were present in the initial set, and 1,779 models that represent fusions of multiple previously incomplete models. In approximately half, 5'-ends were precisely mapped using 5'-full-length ESTs, an important refinement even in otherwise unchanged models. CONCLUSION: Using these new resources, we identify a population of non-canonical (non-GT-AG) introns and also find that approximately 20% of Ciona genes reside in operons and that operons contain a high proportion of single-exon genes. Thus, the present dataset provides an opportunity to analyze the Ciona genome much more precisely than ever.

Evola: Ortholog database of all human genes in H-InvDB with manual curation of phylogenetic trees.

Orthologs are genes in different species that evolved from a common ancestral gene by speciation. Currently, with the rapid growth of transcriptome data of various species, more reliable orthology information is prerequisite for further studies. However, detection of orthologs could be erroneous if pairwise distance-based methods, such as reciprocal BLAST searches, are utilized. Thus, as a sub-database of H-InvDB, an integrated database of annotated human genes (http://h-invitational.jp/), we constructed a fully curated database of evolutionary features of human genes, called 'Evola'. In the process of the ortholog detection, computational analysis based on conserved genome synteny and transcript sequence similarity was followed by manual curation by researchers examining phylogenetic trees. In total, 18 968 human genes have orthologs among 11 vertebrates (chimpanzee, mouse, cow, chicken, zebrafish, etc.), either computationally detected or manually curated orthologs. Evola provides amino acid sequence alignments and phylogenetic trees of orthologs and homologs. In 'd(N)/d(S) view', natural selection on genes can be analyzed between human and other species. In 'Locus maps', all transcript variants and their exon/intron structures can be compared among orthologous gene loci. We expect the Evola to serve as a comprehensive and reliable database to be utilized in comparative analyses for obtaining new knowledge about human genes. Evola is available at http://www.h-invitational.jp/evola/.