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PubMed2004

Update on genome completion and annotations: Protein Information Resource.

The Protein Information Resource (PIR) recently joined the European Bioinformatics Institute (EBI) and Swiss Institute of Bioinformatics (SIB) to establish UniProt--the Universal Protein Resource--which now unifies the PIR, Swiss-Prot and TrEMBL databases. The PIRSF (SuperFamily) classification system is central to the PIR/UniProt functional annotation of proteins, providing classifications of whole proteins into a network structure to reflect their evolutionary relationships. Data integration and associative studies of protein family, function and structure are supported by the iProClass database, which offers value-added descriptions of all UniProt proteins with highly informative links to more than 50 other databases. The PIR system allows consistent, rich and accurate protein annotation for all investigators.

Animals↗
PubMed2025

Chromosome-level genome assembly and annotation of Petunia hybrida.

Petunia hybrida is the world's most popular garden plant and is regarded as a supermodel for studying the biology associated with the Asterid clade, the largest of the two major groups of flowering plants. Unlike other Solanaceae, petunia has a base chromosome number of seven, not 12. This along with recombination suppression has previously hindered efforts to assemble its genome to chromosome level. Here we achieve a chromosome-level assembly for P. hybrida using a combination of short-read and long-read sequencing, optical mapping (Bionano) and Hi-C technologies. The resulting assembly spans 1253.6 Mb with a BUSCO score of 99.8%. A total of 35,089 genes were predicted and of those 29,655 were functionally annotated. Syntenic regions between petunia, tomato and pepper were identified, highlighting rearrangements that have occurred since their divergence indicating that the 12 chromosomes of Solanaceae did not originate from whole genome duplication of an ancestral species with seven chromosomes like petunia. This assembly will enhance trait mapping efficiency and serve as a valuable resource for functional genomic studies.

Petunia↗
PubMed2000

Re-annotating the Mycoplasma pneumoniae genome sequence: adding value, function and reading frames.

Four years after the original sequence submission, we have re-annotated the genome of Mycoplasma pneumoniae to incorporate novel data. The total number of ORFss has been increased from 677 to 688 (10 new proteins were predicted in intergenic regions, two further were newly identified by mass spectrometry and one protein ORF was dismissed) and the number of RNAs from 39 to 42 genes. For 19 of the now 35 tRNAs and for six other functional RNAs the exact genome positions were re-annotated and two new tRNA(Leu) and a small 200 nt RNA were identified. Sixteen protein reading frames were extended and eight shortened. For each ORF a consistent annotation vocabulary has been introduced. Annotation reasoning, annotation categories and comparisons to other published data on M.pneumoniae functional assignments are given. Experimental evidence includes 2-dimensional gel electrophoresis in combination with mass spectrometry as well as gene expression data from this study. Compared to the original annotation, we increased the number of proteins with predicted functional features from 349 to 458. The increase includes 36 new predictions and 73 protein assignments confirmed by the published literature. Furthermore, there are 23 reductions and 30 additions with respect to the previous annotation. mRNA expression data support transcription of 184 of the functionally unassigned reading frames.

Amino Acid Sequence↗
PubMed2004

Java-based application framework for visualization of gene regulatory region annotations.

MOTIVATION: The genome sequences of several organisms are either complete, or being sequenced. Each genome needs to be integrated with various types of annotations, e.g. locations of genes, promoters and other functional elements such as transcriptional regulatory elements. A robust application framework will be useful for developing web-based applications to visualize various genome annotations. RESULTS: We developed genome data visualization toolkit (GDVTK) as an application framework that consists of a set of data structures and core classes, using Java technology. GDVTK is a sound framework for developing web-based applications to present the gene regulatory region annotations in visual form. The current version of GDVTK consists of eight packages and 38 Java classes that are portable, reusable and extensible for plugging in new data sources and models. We implemented GDVTK for visualization of promoter annotations in Mammalian Promoter Database (MPromDb), a web-based gene-regulatory information server. AVAILABILITY: GDVTK is available under GNU general public license. Source code and software documentation can be found at the URL http://bioinformatics.med.ohio-state.edu/GDVTK.

Computer Graphics↗
PubMed2003

Annotation of bacterial genomes using improved phylogenomic profiles.

MOTIVATION: Phylogenomic profiling is a large-scale comparative genomic method used to infer protein function from evolutionary information first described in a binary form by Pellegrini et al. (1999). Here, we propose improvements of this approach including the use of normalized Blastp bit scores, a normalization of the matrix of profiles to take into account the evolutionary distances between bacteria, the definition of a phylogenomic neighborhood based on continuous pairwise distances between genes and an original annotation procedure including the computation of a p-value for each functional assignment. RESULTS: The method presented here increases the number of Ecocyc enzymes identified as being evolutionarily related by about 25% with respect to the original binary form (absent/present) method. The fraction of 'false' positives is shown to be smaller than 20%. Based on their phylogenomic relationships, genes of unknown function can then be automatically related to annotated genes. Each gene annotation predicted is associated with a p-value, i.e. its probability to be obtained by chance. The validity of this method was extensively tested on a large set of genes of known function using the MultiFun database. We find that 50% of 3122 function attributions that can be made at a p-value level of 10(-11) correspond to the actual gene annotation. The method can be readily applied to any newly sequenced microbial genome. In contrast to earlier work on the same topic, our approach avoids the use of arbitrary cut-off values, and provides a reliability estimate of the functional predictions in form of p-values.

Algorithms↗
PubMed2004

[Analysis, identification and correction of some errors of model refseqs appeared in NCBI Human Gene Database by in silico cloning and experimental verification of novel human genes].

We found that human genome coding regions annotated by computers have different kinds of many errors in public domain through homologous BLAST of our cloned genes in non-redundant (nr) database, including insertions, deletions or mutations of one base pair or a segment in sequences at the cDNA level, or different permutation and combination of these errors. Basically, we use the three means for validating and identifying some errors of the model genes appeared in NCBI GENOME ANNOTATION PROJECT REFSEQS: (I) Evaluating the support degree of human EST clustering and draft human genome BLAST. (2) Preparation of chromosomal mapping of our verified genes and analysis of genomic organization of the genes. All of the exon/intron boundaries should be consistent with the GT/AG rule, and consensuses surrounding the splice boundaries should be found as well. (3) Experimental verification by RT-PCR of the in silico cloning genes and further by cDNA sequencing. And then we use the three means as reference: (1) Web searching or in silico cloning of the genes of different species, especially mouse and rat homologous genes, and thus judging the gene existence by ontology. (2) By using the released genes in public domain as standard, which should be highly homologous to our verified genes, especially the released human genes appeared in NCBI GENOME ANNOTATION PROJECT REFSEQS, we try to clone each a highly homologous complete gene similar to the released genes in public domain according to the strategy we developed in this paper. If we can not get it, our verified gene may be correct and the released gene in public domain may be wrong. (3) To find more evidence, we verified our cloned genes by RT-PCR or hybrid technique. Here we list some errors we found from NCBI GENOME ANNOTATION PROJECT REFSEQs: (1) Insert a base in the ORF by mistake which causes the frame shift of the coding amino acid. In detail, abase in the ORF of a gene is a redundant insertion, which causes a reading frame shift in the translation of an alternative protein, such as LOC124919 is wrong form of C17 orf32 (with mouse and rat orthologs determined by us). (2) Put together by mistake (with force). This is a wrong assembly of non-relating cDNA segment, such as LOC147007 is wrong form of C17orf32. (3) Mistakenly insert a base or one section of cDNA in the ORF which causes it ending beforehand, only coding cDNA sequence of N-terminal amino acids, incomplete. For example, LOC123722 is wrong form of SPRYD1, and even the human hypothetical gene LOC126250 or PDCD5 is wrong form of our PDCD5 (TFAR19). (4) Incomplete, only coding cDNA sequence of C-terminal amino acids. For example, human LOC149076 and mouse LOC230761 are wrong form of our verified human ZNF362 and mouse Zfp362, respectively. (5) Incomplete, only coding one section of coding protein cDNA sequence of correct gene ORF, lacking N-terminal and C-terminal amino acids sequence, and at the same time, mistakenly anticipates the first non-initiation codon amino acid of the incomplete protein amino acid as the initiation codon, e.g. anticipating L as M. For example, LOC200084 is wrong form of ZNF362. (6) Mistakenly insert a base or one section of cDNA in the ORF, wrongly causing unwanted termination codon before the insertion, so the coding protein lacks the first part of the amino acids. For example, the GenBank Acc. No. AL096883 ( LOCUS No. HS323M22B) is wrong form of an experimentally verified human NM_012263 with mouse ortholog of BC010510 determined. (7) It may regard the polluted genomic sequence as complete gene cDNA sequence and anticipate the so-called single exon gene, even the real one, only a small ORF in the very long single exon mRNA, while there really exists termination code in the same phase of the upper part of the ORF initiation code, no other characters accord with the gene's condition. For example, LOC91126 is wrong form of ZNF362. (8) The anticipated genes only have ORF which has no EST proofs on both terminal sides. Depending on this ORF, a complete gene cDNA with double support of EST and human genome (there are termination codes at the same phase of the upper part of ORF) which indicates the anticipated ORF reference sequence may be incorrect. For example, LOC164395 may be wrong form of novel human gene bankit4590055. (9) A similar but smaller protein-coding gene is anticipated in the range of the human genome sequence that has the support of EST experimental proof, so other new anticipated gene may be incorrect. For example, LOC167563 may be wrong form of CMYA5. However,these errors can be corrected or avoided by using our strategy. Here we give one example in detail: Comparision of the sequence SPRYD1 with human hypothetical gene LOC123722. The TAA bases in the position of 478-480 in LOC123722 cDNA is redundant, which causes a reading frame shift in the translation of an alternative protein. The redundancy of GTAAA of LOC123722 is not supported by our experimental clone,and is almost fully rejected by human EST alignment, and is shown as the next intron sequence by genomic GT/AG organization analysis. The verification of cDNA or genomic DNA sequence of SPRYD1 implies that LOC123722 has a wrong stop codon within its ORF because of the prediction program, thus being not complete cds. To sum up, by combining bioinformatics analyses with experimental verification, we have found that there are many errors of at least nine kinds appeared in NCBI GENOME ANNOTATION PROJECT REFSEQs through BLAST of our cloned genes in non-redundant database, and our strategy is helpful in correcting them, such as LOC14907, LOC200084 and LOC91126 (all of them should be ZNF362, but are three different kinds of wrong forms of ZNF362), three model reference sequences predicted from NCBI contig NT_004511 by automated computational analysis using gene prediction method, or such as LOC124919 and LOC147007 (both should be C17orf32, but are two different kinds of wrong forms of C17orf32), two model reference sequences predicted from NCBI contig NT_010808 by automated computational analysis using gene prediction method. Therefore, the correct identification and annotation of novel human genes may be still a heavy task, which can be finished within a long period of time. So human genome coding regions annotated by computer should be used with caution. The articles published in the past did not clearly point out the existence of mistakes in the NCBI human gene mode reference sequence. At the Seventh International Human Genome Conference held in April 2002, we first published the researching result on this aspect in the communication form of Posterly insert a base or one section of cDNA in the ORF, wrongly causing unwanted termination codon before the insertion, so the coding protein lacks the first part of the amino acids. For example, the GenBank Acc. No. AL096883 ( LOCUS No. HS323M22B) is wrong form of an experimentally verified human NM_012263 with mouse ortholog of BC010510 determined. (7) It may regard the polluted genomic sequence as complete gene cDNA sequence and anticipate the so-called single exon gene, even the real one, only a small ORF in the very long single exon mRNA, while there really exists termination code in the same phase of the upper part of the ORF initiation code, no other characters accord with the gene's condition. For example, LOC91126 is wrong form of ZNF362. (8) The anticipated genes only have ORF which has no EST proofs on both terminal sides. Depending on this ORF, a complete gene cDNA with double support of EST and human genome (there are termination codes at the same phase of the upper part of ORF) which indicates the anticipated ORF reference sequence may be incorrect. For example, LOC164395 may be wrong form of novel human gene bankit4590055. (9) A similar but smaller protein-coding gene is anticipated in the range of the human genome sequence that has the support of EST experimental proof, so other new anticipated gene may be incorrect. For example, LOC167563 may be wrong form of CMYA5. However, these errors can be corrected or avoided by using our strategy. Here we give one example in detail: Comparision of the sequence SPRYD1 with human hypothetical gene LOC123722. The TAA bases in the position of 478-480 in LOC123722 cDNA is redundant, which causes a reading frame shift in the translation of an alternative protein. The redundancy of GTAAA of LOC123722 is not supported by our experimental clone, and is almost fully rejected by human EST alignment, and is shown as the next intron sequence by genomic GT/AG organization analysis. The verification of cDNA or genomic DNA sequence of SPRYD1 implies that LOC123722 has a wrong stop codon within its ORF because of the prediction program, thus being not complete cds. To sum up, by combining bioinformatics analyses with experimental verification, we have found that there are many errors of at least nine kinds appeared in NCBI GENOME ANNOTATION PROJECT REFSEQs through BLAST of our cloned genes in non-redundant database, and our strategy is helpful in correcting them, such as LOC14907, LOC200084 and LOC91126 (all of them should be ZNF362, but are three different kinds of wrong forms of ZNF362), three model reference sequences predicted from NCBI contig NT_004511 by automated computational analysis using gene prediction method, or such as LOC124919 and LOC147007 (both should be C17orf32, but are two different kinds of wrong forms of C17orf32), two model reference sequences predicted from NCBI contig NT_010808 by automated computational analysis using gene prediction method. Therefore, the correct identification and annotation of novel human genes may be still a heavy task, which can be finished within a long period of time. So human genome coding regions annotated by computer should be used with caution. (ABSTRACT TRUNCATED)

Amino Acid Sequence↗
PubMed2004

A Bayesian method for identifying missing enzymes in predicted metabolic pathway databases.

BACKGROUND: The PathoLogic program constructs Pathway/Genome databases by using a genome's annotation to predict the set of metabolic pathways present in an organism. PathoLogic determines the set of reactions composing those pathways from the enzymes annotated in the organism's genome. Most annotation efforts fail to assign function to 40-60% of sequences. In addition, large numbers of sequences may have non-specific annotations (e.g., thiolase family protein). Pathway holes occur when a genome appears to lack the enzymes needed to catalyze reactions in a pathway. If a protein has not been assigned a specific function during the annotation process, any reaction catalyzed by that protein will appear as a missing enzyme or pathway hole in a Pathway/Genome database. RESULTS: We have developed a method that efficiently combines homology and pathway-based evidence to identify candidates for filling pathway holes in Pathway/Genome databases. Our program not only identifies potential candidate sequences for pathway holes, but combines data from multiple, heterogeneous sources to assess the likelihood that a candidate has the required function. Our algorithm emulates the manual sequence annotation process, considering not only evidence from homology searches, but also considering evidence from genomic context (i.e., is the gene part of an operon?) and functional context (e.g., are there functionally-related genes nearby in the genome?) to determine the posterior belief that a candidate has the required function. The method can be applied across an entire metabolic pathway network and is generally applicable to any pathway database. The program uses a set of sequences encoding the required activity in other genomes to identify candidate proteins in the genome of interest, and then evaluates each candidate by using a simple Bayes classifier to determine the probability that the candidate has the desired function. We achieved 71% precision at a probability threshold of 0.9 during cross-validation using known reactions in computationally-predicted pathway databases. After applying our method to 513 pathway holes in 333 pathways from three Pathway/Genome databases, we increased the number of complete pathways by 42%. We made putative assignments to 46% of the holes, including annotation of 17 sequences of previously unknown function. CONCLUSIONS: Our pathway hole filler can be used not only to increase the utility of Pathway/Genome databases to both experimental and computational researchers, but also to improve predictions of protein function.

Amino Acid Oxidoreductases↗
PubMed2005

Protozoan genomes: gene identification and annotation.

The draft sequence of several complete protozoan genomes is now available and genome projects are ongoing for a number of other species. Different strategies are being implemented to identify and annotate protein coding and RNA genes in these genomes, as well as study their genomic architecture. Since the genomes vary greatly in size, GC-content, nucleotide composition, and degree of repetitiveness, genome structure is often a factor in choosing the methodology utilised for annotation. In addition, the approach taken is dictated, to a greater or lesser extent, by the particular reasons for carrying out genome-wide analyses and the level of funding available for projects. Nevertheless, these projects have provided a plethora of material that will aid in understanding the biology and evolution of these parasites, as well as identifying new targets that can be used to design urgently required drug treatments for the diseases they cause.

Algorithms↗
PubMed2006

TcruziDB: an integrated, post-genomics community resource for Trypanosoma cruzi.

TcruziDB (http://TcruziDB.org) is an integrated post-genomics database for the parasitic organism, Trypanosoma cruzi, the causative agent of Chagas' disease. TcruziDB was established in 2003 as a flat-file database with tools for mining the unannotated sequence reads and preliminary contig assemblies emerging from the Tri-Tryp genome consortium (TIGR/SBRI/Karolinska). Today, TcruziDB houses the recently published assembled genomic contigs and annotation provided by the genome consortium in a relational database supported by the Genomics Unified Schema (GUS) architecture. The combination of an annotated genome and a relational architecture has facilitated the integration of genomic data with expression data (proteomic and EST) and permitted the construction of automated analysis pipelines. TcruziDB has accepted, and will continue to accept the deposition of genomic and functional genomic datasets contributed by the research community.

Animals↗
PubMed2005

GARSA: genomic analysis resources for sequence annotation.

SUMMARY: Growth of genome data and analysis possibilities have brought new levels of difficulty for scientists to understand, integrate and deal with all this ever-increasing information. In this scenario, GARSA has been conceived aiming to facilitate the tasks of integrating, analyzing and presenting genomic information from several bioinformatics tools and genomic databases, in a flexible way. GARSA is a user-friendly web-based system designed to analyze genomic data in the context of a pipeline. EST and GGS data can be analyzed using the system since it accepts (1) chromatograms, (2) download of sequences from GenBank, (3) Fasta files stored locally or (4) a combination of all three. Quality evaluation of chromatograms, vector removing and clusterization are easily performed as part of the pipeline. A number of local and customizable Blast and CDD analyses can be performed as well as Interpro, complemented with phylogeny analyses. GARSA is being used for the analyses of Trypanosoma vivax (GSS and EST), Trypanosoma rangeli (GSS, EST and ORESTES), Bothrops jararaca (EST), Piaractus mesopotamicus (EST) and Lutzomyia longipalpis (EST). AVAILABILITY: The GARSA system is freely available under GPL license (http://www.biowebdb.org/garsa/). For download requests visit http://www.biowebdb.org/garsa/ or contact Dr Alberto Dávila.

Animals↗
PubMed2004

Subfunction partitioning, the teleost radiation and the annotation of the human genome.

Half of all vertebrate species are teleost fish. What accounts for this explosion of biodiversity? Recent evidence and advances in evolutionary theory suggest that genomic features could have played a significant role in the teleost radiation. This review examines evidence for an ancient whole-genome duplication (tetraploidization) event that probably occurred just before the teleost radiation. The partitioning of ancestral subfunctions between gene copies arising from this duplication could have contributed to the genetic isolation of populations, to lineage-specific diversification of developmental programs, and ultimately to phenotypic variation among teleost fish. Beyond its importance for understanding mechanisms that generate biodiversity, the partitioning of subfunctions between teleost co-orthologs of human genes can facilitate the identification of tissue-specific conserved noncoding regions and can simplify the analysis of ancestral gene functions obscured by pleiotropy or haploinsufficiency. Applying these principles on a genomic scale can accelerate the functional annotation of the human genome and understanding of the roles of human genes in health and disease.

Animals↗
PubMed2006

PUMA2--grid-based high-throughput analysis of genomes and metabolic pathways.

The PUMA2 system (available at http://compbio.mcs.anl.gov/puma2) is an interactive, integrated bioinformatics environment for high-throughput genetic sequence analysis and metabolic reconstructions from sequence data. PUMA2 provides a framework for comparative and evolutionary analysis of genomic data and metabolic networks in the context of taxonomic and phenotypic information. Grid infrastructure is used to perform computationally intensive tasks. PUMA2 currently contains precomputed analysis of 213 prokaryotic, 22 eukaryotic, 650 mitochondrial and 1493 viral genomes and automated metabolic reconstructions for >200 organisms. Genomic data is annotated with information integrated from >20 sequence, structural and metabolic databases and ontologies. PUMA2 supports both automated and interactive expert-driven annotation of genomes, using a variety of publicly available bioinformatics tools. It also contains a suite of unique PUMA2 tools for automated assignment of gene function, evolutionary analysis of protein families and comparative analysis of metabolic pathways. PUMA2 allows users to submit batch sequence data for automated functional analysis and construction of metabolic models. The results of these analyses are made available to the users in the PUMA2 environment for further interactive sequence analysis and annotation.

Computational Biology↗
PubMed2002

Functional annotation of mammalian genomic DNA sequence by chemical mutagenesis: a fine-structure genetic mutation map of a 1- to 2-cM segment of mouse chromosome 7 corresponding to human chromosome 11p14-p15.

Eleven independent, recessive, N-ethyl-N-nitrosourea-induced mutations that map to a approximately 1- to 2-cM region of mouse chromosome (Chr) 7 homologous to human Chr 11p14-p15 were recovered from a screen of 1,218 gametes. These mutations were initially identified in a hemizygous state opposite a large p-locus deletion and subsequently were mapped to finer genomic intervals by crosses to a panel of smaller p deletions. The 11 mutations also were classified into seven complementation groups by pairwise crosses. Four complementation groups were defined by seven prenatally lethal mutations, including a group (l7R3) comprised of two alleles of obvious differing severity. Two allelic mutations (at the psrt locus) result in a severe seizure and runting syndrome, but one mutation (at the fit2 locus) results in a more benign runting phenotype. This experiment has added seven loci, defined by phenotypes of presumed point mutations, to the genetic map of a small (1-2 cM) region of mouse Chr 7 and will facilitate the task of functional annotation of DNA sequence and transcription maps both in the mouse and the corresponding human 11p14-p15 homology region.

Animals↗
PubMed2005

The domain architecture of large guanine nucleotide exchange factors for the small GTP-binding protein Arf.

BACKGROUND: Small G proteins, which are essential regulators of multiple cellular functions, are activated by guanine nucleotide exchange factors (GEFs) that stimulate the exchange of the tightly bound GDP nucleotide by GTP. The catalytic domain responsible for nucleotide exchange is in general associated with non-catalytic domains that define the spatio-temporal conditions of activation. In the case of small G proteins of the Arf subfamily, which are major regulators of membrane trafficking, GEFs form a heterogeneous family whose only common characteristic is the well-characterized Sec7 catalytic domain. In contrast, the function of non-catalytic domains and how they regulate/cooperate with the catalytic domain is essentially unknown. RESULTS: Based on Sec7-containing sequences from fully-annotated eukaryotic genomes, including our annotation of these sequences from Paramecium, we have investigated the domain architecture of large ArfGEFs of the BIG and GBF subfamilies, which are involved in Golgi traffic. Multiple sequence alignments combined with the analysis of predicted secondary structures, non-structured regions and splicing patterns, identifies five novel non-catalytic structural domains which are common to both subfamilies, revealing that they share a conserved modular organization. We also report a novel ArfGEF subfamily with a domain organization so far unique to alveolates, which we name TBS (TBC-Sec7). CONCLUSION: Our analysis unifies the BIG and GBF subfamilies into a higher order subfamily, which, together with their being the only subfamilies common to all eukaryotes, suggests that they descend from a common ancestor from which species-specific ArfGEFs have subsequently evolved. Our identification of a conserved modular architecture provides a background for future functional investigation of non-catalytic domains.

ADP-Ribosylation Factors↗
PubMed2000

Comparison of functional annotation schemes for genomes.

In this paper we survey a number of functional classification schemes applicable to genomes. We present the concepts of depth, breadth and resolution as descriptors of the schemes' scope and architecture and compare selected classifications according to these criteria. We also generate a 'Combined Scheme' against which we map six classifications which we believe are representative of the range currently available. The mapping allows the generation of 'FuncWheels', which are graphical representations of hierarchical classification schemes. They are used to illustrate similarities and differences in functional space coverage. This survey highlights many issues related to the design and implementation of gene product functional classifications, which are discussed in the light of emerging 'second-generation' schemes.

Animals↗
PubMed2004

Annotating the Plasmodium genome and the enigma of the shikimate pathway.

The completion of the Plasmodium falciparum genome sequence heralds a new era in the effort to identify all the parasite's genes along with their cellular functions. A combination of bioinformatics and experimental proof will facilitate this process. Many enzymes in metabolic processes have been identified, but several examples exist of incomplete pathways, such as the shikimate pathway. This review uses the example of the shikimate pathway to examine the application of bioinformatics to lead experimental design in post-genomic biology.

Amino Acid Sequence↗
PubMed2001

Computational methods for gene annotation: the Arabidopsis genome.

Since the structure of the DNA molecule was identified half a century ago, the complete genome sequence has been determined for 37 prokaryotes and several eukaryotes. With the exponential growth of genetic information, bioinformatics has attempted to predict gene locations and functions in cyberspace prior to experimental confirmation at the bench.

Arabidopsis↗