Logo of narLink to Publisher's site
Nucleic Acids Res. Jan 2012; 40(Database issue): D1178–D1186.
Published online Nov 22, 2011. doi:  10.1093/nar/gkr944
PMCID: PMC3245001

Phytozome: a comparative platform for green plant genomics

Abstract

The number of sequenced plant genomes and associated genomic resources is growing rapidly with the advent of both an increased focus on plant genomics from funding agencies, and the application of inexpensive next generation sequencing. To interact with this increasing body of data, we have developed Phytozome (http://www.phytozome.net), a comparative hub for plant genome and gene family data and analysis. Phytozome provides a view of the evolutionary history of every plant gene at the level of sequence, gene structure, gene family and genome organization, while at the same time providing access to the sequences and functional annotations of a growing number (currently 25) of complete plant genomes, including all the land plants and selected algae sequenced at the Joint Genome Institute, as well as selected species sequenced elsewhere. Through a comprehensive plant genome database and web portal, these data and analyses are available to the broader plant science research community, providing powerful comparative genomics tools that help to link model systems with other plants of economic and ecological importance.

INTRODUCTION

Plant genome databases have grown up around different plant clades [e.g. TAIR for Arabidopsis (1), Gramene for grasses (2), SGN for Solanaceae (3), GDR for Rosaceae (4), LIS for legumes (5)]. This is in part due to the longstanding investment in plant genetic and physical mapping resources and the focus of breeding programs in different agricultural crops. Comparative genomic databases that sample widely across the Viridiplantae [Phytozome, GreenPhylDB (6), Plaza (7), PlantGDB (8)] are a more recent development. These databases and associated web portals provide, at a minimum, a uniform set of tools and automated analyses across a wider range of plant genomes. In addition, those focused on green plant comparative genomics (GreenPhylDB, Plaza and Phytozome) provide putative gene families (groups of extant genes descended from a common ancestral gene) calculated at one or more speciation nodes in the plant tree of life, spanning most if not all hosted species, as well as additional gene-centric and genome-centric comparative tools. Their goal is to provide a platform for both genome-informed investigations of plant evolution, as well as a framework for transferring functional information from model plants to plants of agricultural, industrial and environmental importance.

Phytozome ((http://www.phytozome.net), first released in 2008, provides a centralized hub that enables users with varying degrees of computational sophistication to access annotated plant gene families, to navigate the evolutionary history of gene families and individual genes, to examine plant genes in their genomic context, to assign putative function to uncharacterized user sequences and provides uniform access to plant genomics data sets consisting of complete genomes, gene and related (e.g. homologous) sequences and alignments, gene functional information and gene families, either in bulk or as the result of on-the-fly complex queries. The Phytozome web portal integrates a number of widely-used open source components [Lucene, GBrowse (9), Jalview (10), BioMart (11), mView (12) and pygr] with custom visualization code for gene family search, inspection and evaluation.

DATA SOURCES AND STANDARD ANALYSES

The v7.0 release of Phytozome contains data and analyses for 25 plant genomes, 18 of which were sequenced, assembled and partially or completely annotated at the JGI (Table 1). The gene-calling procedure for each JGI genome is described in detail in the associated genome publication, but a general overview of the JGI Plant Genome Annotation workflow is provided in Supplementary Methods S1. For non-JGI genomes and annotations, assembled genome sequences and gene, transcript and peptide information is obtained in GFF or FASTA format, and subjected to consistency checking.

Table 1.
The 25 completed plant genomes in version 7 of Phytozome

For non-JGI genomes, any gene symbols, database cross references, deflines and experimentally-supported functional annotations (e.g. GO, EC) are also obtained. In the interests of uniformity of functional annotation, automatically generated functional annotations of non-JGI genomes are not retained. Protein-coding genes from both JGI and non-JGI genomes are then assigned PFAM domains (26), KEGG enzyme classification and KEGG Orthology assignment (27), KOG assignment (28) and Panther classification (29). Gene Ontology (GO) (30) assignments are made via pfam2GO mapping (31). All gene models and associated annotations are then loaded into Phytozome's mySQL database.

Same-species and near-species EST assemblies and Phytozome plant peptides are aligned against each genome. Each genome also undergoes whole genome alignment against a clade-informative subset of the other Phytozome genomes using the VISTA pipeline (32). Gene and alignment tracks, as well as VISTA-derived genome-wide pairwise DNA alignments are all accessible from Phytozome's GBrowse genome browser.

GENE FAMILY CONSTRUCTION

Large scale, automated gene family construction is typically based on distance methods [Phytome (33), PlantTribes (34), InParanoid (35), OrthoMCL (36)] or, less frequently, distance-plus-character methods [OrthologID (37), TreeFam (38)], using a single peptide per locus in each genome under consideration. These distance-based methods can be broadly separated into two categories: those that implicitly (OrthoMCL) or explicitly (InParanoid) take into account the Mutual Best Hit (MBH) (39) relationship between putatively orthologous sequences and its role in setting a threshold for paralog accumulation (Supplementary Methods S2), and those that do not (Phytome, PlantTribes).

Distance-based methods have the advantage of being generally fast and scalable. Their main disadvantage lies in their reliance on a single score to characterize the evolutionary divergence of sequences, which becomes more problematic when considering species with an ancient divergence (in which case BLASTP scores tend to lose their resolving power, leading to the either the accumulation of unrelated, weakly aligning sequences into families at low significance thresholds, or the exclusion of distant but true homologs at higher significance thresholds).

Distance-plus-character-based methods use distance scores and a simple threshold to build an initial set of gene proto-families, all of whose members are more similar to each other than the threshold (e.g. OrthologID currently employs an E-value threshold of 1e  20). The members of each family are then included in a multiple sequence alignment (MSA), and phylogenetic trees are constructed based on discriminating residues (characters) in the MSA. The actual gene families correspond to the various monophyletic nodes found in the resulting trees. Phylogenetic methods are traditionally thought to be more accurate, especially when looking at anciently diverged species. However, recent work (40) on Drosophila and fungal species that span evolutionary distances comparable to the eudicots, has shown that a wide range of tree-building methods fail >50% of the time to produce the correct tree topology for even simple gene families, indicating the need for caution when making ortholog/paralog assignments based on gene and species tree reconciliation.

Whatever construction method is chosen, each gene family and its associated phylogenetic tree represents a hypothesis of the evolutionary history of a set of extant genes, presumed to be descendants of a single, unobservable ancestral gene. Descendants arise either via speciation (giving rise to orthologous descendants) or local or larger scale duplication events (giving rise to paralogous descendants). As orthologs are assumed to more likely share a common biological function, while paralogs are subject to both neo- and subfunctionalization (41,42), the high confidence identification of orthologs allows for the transfer of functional information from well-studied, tractable model systems (e.g. Arabidopsis and Brachypodium) to other economically or otherwise relevant plants.

Gene family construction in Phytozome uses a distance-based approach similar to the PhiGs method (43), the initial proto-family creation step used in TreeFam, with several modifications (Supplementary Methods S2). Family construction is restricted initially to a subset of core genomes, which are assumed to have relatively stable assemblies and complete structural annotations, though in some cases genomes with draft assemblies and annotations are used if the species in question is the sole representative of its clade (e.g. Selaginella, Physcomitrella, Mimulus). Using the assumed species tree, gene families are constructed at each evolutionary node, starting from the crown nodes [as in (44)] and moving backward in evolutionary time. At each bifurcating parent node, pairs of gene families from the two daughter nodes are combined into a parent family if they are joined by a cross-node MBH. Remaining families from the daughter nodes will be added to a parent family as paralogs if they have a hit to the parent that is stronger than the parent's best outgroup hit. This process is repeated down to the root node. MSAs from MUSCLE (45) and Hidden Markov Model (HMM) profiles from HMMER3 (46) are created for each core family. These profiles are used to ‘pledge’ peptides from non-core genomes into existing core families using HMMScan (46); they can also join core families if they are linked by a MBH. Non-core members can pledge to multiple families at a given node; thus the strict nesting of gene families is true for the core members only.

Figure 1 shows a typical gene family view, with the basis for each gene's membership in the family displayed in the leftmost column. A view of this family's evolutionary history (Figure 2) shows the hierarchical nesting of the core families.

Figure 1.
Default view of the Gene Family page for a 17 member core eudicot family. Members are listed according to their order in the tree on the Phytozome home page. The membership class of each gene is indicated in the leftmost column (Supplementary Methods ...
Figure 2.
Family History view of the gene family in Figure 1. All the descendants and ancestors of this core eudicot family (which is highlighted) are visible in the history view. The strict nesting of families is observed, though one needs to remember that one ...

The use of relatively strict significance and coverage thresholds, as well as an insistence on MBH relationships rather than simply strong similarity as the basis for seeding gene families, is intended to prevent merely similar gene families from coalescing at an inappropriate node in the tree. It also, however, biases Phytozome families towards underclustering. For this reason Phytozome includes a number of search and navigation tools, described below, to quickly bring together gene families that share overall sequence similarity or functional annotation.

PHYTOZOME TOOLS AND VIEWS

Text and sequence search

Genes and gene families can be retrieved from Phytozome by both keyword and sequence similarity searches. BLAST and BLAT searches of organism genomes, and BLAST searches of proteomes and gene family consensus sequences, can be used to find the genomic regions, gene transcripts, peptides and gene families most similar to a given query sequence. All gene and gene family attributes such as names, symbols, synonyms, external database identifiers, deflines and functional annotation ids (e.g. PFAM00071, E.C. 1.1.1.95) are searchable, and gene families automatically inherit the attributes of their members, making it straightforward to retrieve a family of related but mostly uncurated genes as long as at least one family member is well annotated. Search can be restricted to gene families at a particular evolutionary node, and to families matching particular absence/presence phylogenetic profiles. One can also search the database of functional annotations (e.g. keywords from the descriptions of PFAM, GO, KEGG, KOG, Panther), which retrieves the set of all matching functional identifiers, and then automatically performs a second search for families marked as containing those functions.

All genes and gene families found via keyword or sequence similarity searches can be viewed individually, as described below, or first combined ‘on the fly’ to produce composite families, before being viewed and analyzed with the same tools used for individual families.

Gene family and gene page views

The Gene Family view (Figure 1) provides the user with detailed information on each family and its constituent members, organized to highlight shared attributes. The default ‘Genes in this family’ tab displays individual family members, grouped by species and includes each member's source identifier (hyperlinked to the appropriate source database), aliases, synonyms and gene symbols, deflines (where available) and a graphical view of each member's local syntenic environment. A provisional family name is provided, as well as a membership ‘fingerprint’ (member count for all species present at this node), and family-level KOG and KEGG-Orthology classification. The syntenic display can be replaced by a PFAM domain or gene structure (exon/intron) display. For each family member, links are provided to both a GBrowse view (Figure 3) of each gene in its genomic context, and a ‘Gene Page’ (Figure 4).

Figure 3.
GBrowse view of the local genomic context of the poplar gene from the family in Figure 1. Primary and alternative transcripts (if present), assembled EST data and related plant peptides are shown aligned against the genome. Not shown are tracks of repetitive ...
Figure 4.
Default view of the Gene Page for the Arabidopsis thaliana gene in the family of Figure 1, showing primary transcript info, functional annotations and simplified genomic context. This locus has an alternative transcript (which appears to differ primarily ...

The family page is divided into a set of lower and upper tabs, roughly corresponding to ‘information’ and ‘actions’, respectively. The lower row helps users explore the consistency and evolutionary history of the family. The ‘Functional Annotation’ tab lists all the functional and domain annotations (e.g. PFAM, Panther, GO, KEGG, KEGG Orthology) assigned to family members, broken down by organism. Functional annotations present in all family members are highlighted. The ‘MSA’ tab displays a pre-computed MUSCLE peptide alignment of all family members, which is downloadable. The family's evolutionary history can be viewed in the ‘Family History’ tab, where all families that are parents of, or derived from, the current family are listed. From the upper row of tabs, ‘Find related families’ provides a number of methods for identifying families similar to the current one: by family consensus sequence similarity, by shared functional annotation, or by shared gene membership. This is quite useful when looking for related subfamilies, or verifying that a particular combination of domains is unique to a given family. ‘Align family members’ forwards family member coding or peptide sequences directly to the Jalview tool, where MSAs can be created and edited, and subsequently used to construct phylogenetic trees. ‘Get Data’ provides access to the BioMart data query tool for this family, while the family page display can be customized on the ‘Display options’ tab.

The Gene Page (Figure 4), in addition to showing single gene functional annotations and evolutionary history, includes links to alternatively spliced transcripts (if they exist), a simplified view of the gene in its genomic context (showing alternatively spliced transcripts and peptide homology tracks), direct access to genomic, transcript, coding and peptide sequences associated with this gene locus (color-coded to indicate exon/intron and UTR boundaries), and a graphical view of all other Phytozome peptides aligned [via dual affine Smith-Waterman (47)] against this gene's peptide.

Genome-centric views are provided by GBrowse (Figure 3) for all 25 genomes currently included in Phytozome. The browsers can be accessed directly from the Phytozome home page, from individual member gene links on the Gene Family or Gene page, and from the BLAST/BLAT results page for searches performed against one of the genome target databases. In the latter two cases, a zoomed-in view of the genomic region containing the selected gene (or BLAST hit) is displayed. Each browser typically displays a gene prediction track (primary and alternatively spliced transcripts), a track of homologous peptides from related species aligned against the genome, supporting EST (or EST assemblies) and one or more VISTA tracks identifying regions of this genome that are syntenic with other plant genomes included in Phytozme. All gene features are hyperlinked to their respective Gene Page, while the VISTA tracks are linked to the corresponding genomic regions in the VISTA browser.

DATA ACCESS

For each genome hosted at Phytozome, bulk data files are available that contain genome assembly sequence, gene structure GFF3, transcript, coding and peptide sequence in FASTA format and general annotation information (PFAM, Panther, KOG, KEGG, best rice and Arabidopsis homologs). For JGI genomes, we also provide repeat-masked genome assemblies, as well as supporting annotation data (e.g. the PASA EST assemblies used in gene calling).

Customized data sets consisting of gene or gene family sequences and annotations can be constructed using Phytozome's implementation of BioMart, where users can choose detailed data filters, attributes and output formats. BioMart can be accessed from the ‘Get Data’ tab on a gene family page (in which case the data is, by default, initially restricted to that gene family), or directly from the Phytozome menu. It is also available at the BioMart central portal, http://www.biomart.org.

PHYTOZOME SOFTWARE IMPLEMENTATION

We have made extensive reuse of available databases, software tools and data formats in our implementation of Phytozome. The Phytozome website is built on a LAMPJ stack (Linux, Apache, mySQL, php/Perl and Java). Open source visualization components of Phytozome include: Gbrowse (9), the Generic Genome Browser, from the GMOD project, for the visualization of features in their genomic context; Jalview (10), a multiple alignment viewer and editor, for the creation, detailed inspection and modification of MSAs and phylogenetic trees; BioMart (11), to enable query-based downloads of bulk data on gene families and genome annotations; BioPerl (48), for the parsing and formatting of genomic data and BLAST results; and mView (12), for the visualization of MSAs. The search system is based on the Lucene search engine (http://lucene.apache.org/).

FUTURE PLANS

Phytozome content will continue to be updated at least annually, with new and updated genomes typically added in January and new feature sets released quarterly. Current plans for the January 2012 (v8) release include updates to poplar, soybean, brachypodium, maize and medicago, the first-time inclusion of the JGI genomes phaseolus (common bean) and Capsella rubella (an Arabidopsis comparator), and the externally contributed apple (49), strawberry (50) and potato (51) genomes. Version 8 is also expected to include genomic variation data (SNPs and structural variants) from the JGI and elsewhere, and expression data associated with the JGI Gene Atlas projects. Phytozome is also in the final stages of licensing for distribution to end users. We expect that the entire database and software infrastructure will be available for download by the end of 2011.

SUPPLEMENTARY DATA

Supplementary Data are available at NAR Online: Supplementary methods S1–S2, Supplementary references [52–57].

FUNDING

This work was performed at the U.S. Department of Energy Joint Genome Institute, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. Additional funding was provided by the Gordon and Betty Moore Foundation. Funding for open access charge: Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

Conflict of interest statement. None declared.

REFERENCES

1. Swarbreck D, Wilks C, Lamesch P, Berardini TZ, Garcia-Hernandez M, Foerster H, Li D, Meyer T, Muller R, Ploetz L, et al. The Arabidopsis Information Resource (TAIR): gene structure and function annotation. Nucleic Acids Res. 2008;36:D1009–D1014. [PMC free article] [PubMed]
2. Liang C, Jaiswal P, Hebbard C, Avraham S, Buckler ES, Casstevens T, Hurwitz B, McCouch S, Ni J, Pujar A, et al. Gramene: a growing plant comparative genomics resource. Nucleic Acids Res. 2008;36:D947–D953. [PMC free article] [PubMed]
3. Bombarely A, Menda N, Tecle IY, Buels RM, Strickler S, Fischer-York T, Pujar A, Leto J, Gosselin J, Mueller LA. The sol genomics network (solgenomics.net): growing tomatoes using Perl. Nucleic Acids Res. 2011;39:D1149–D1155. [PMC free article] [PubMed]
4. Jung S, Staton M, Lee T, Blenda A, Svancara R, Abbott A, Main D. GDR (Genome Database for Rosaceae): integrated web-database for Rosaceae genomics and genetics data. Nucleic Acids Res. 2008;36:D1034–D1040. [PMC free article] [PubMed]
5. Gonzales MD, Archuleta E, Farmer A, Gajendran K, Grant D, Shoemaker R, Beavis WD, Waugh ME. The Legume Information System (LIS): an integrated information resource for comparative legume biology. Nucleic Acids Res. 2005;33:D660–D665. [PMC free article] [PubMed]
6. Conte MG, Gaillard S, Lanau N, Rouard M, Perin C. GreenPhylDB: a database for plant comparative genomics. Nucleic Acids Res. 2008;36:D991–D998. [PMC free article] [PubMed]
7. Proost S, Van Bel M, Sterck L, Billiau K, Van Parys T, Van de Peer Y, Vandepoele K. PLAZA: a comparative genomics resource to study gene and genome evolution in plants. Plant Cell. 2009;21:3718–3731. [PMC free article] [PubMed]
8. Duvick J, Fu A, Muppirala U, Sabharwal M, Wilkerson MD, Lawrence CJ, Lushbough C, Brendel V. PlantGDB: a resource for comparative plant genomics. Nucleic Acids Res. 2008;36:D959–D965. [PMC free article] [PubMed]
9. Stein LD, Mungall C, Shu S, Caudy M, Mangone M, Day A, Nickerson E, Stajich JE, Harris TW, Arva A, et al. The generic genome browser: a building block for a model organism system database. Genome Res. 2002;12:1599–1610. [PMC free article] [PubMed]
10. Waterhouse AM, Procter JB, Martin DM, Clamp M, Barton GJ. Jalview Version 2–a multiple sequence alignment editor and analysis workbench. Bioinformatics. 2009;25:1189–1191. [PMC free article] [PubMed]
11. Smedley D, Haider S, Ballester B, Holland R, London D, Thorisson G, Kasprzyk A. BioMart–biological queries made easy. BMC Genomics. 2009;10:22. [PMC free article] [PubMed]
12. Brown NP, Leroy C, Sander C. MView: a web-compatible database search or multiple alignment viewer. Bioinformatics. 1998;14:380–381. [PubMed]
13. Hu TT, Pattyn P, Bakker EG, Cao J, Cheng JF, Clark RM, Fahlgren N, Fawcett JA, Grimwood J, Gundlach H, et al. The Arabidopsis lyrata genome sequence and the basis of rapid genome size change. Nat. Genet. 2011;43:476–481. [PMC free article] [PubMed]
14. Initiative IB. Genome sequencing and analysis of the model grass Brachypodium distachyon. Nature. 2010;463:763–768. [PubMed]
15. Ming R, Hou S, Feng Y, Yu Q, Dionne-Laporte A, Saw JH, Senin P, Wang W, Ly BV, Lewis KL, et al. The draft genome of the transgenic tropical fruit tree papaya (Carica papaya Linnaeus) Nature. 2008;452:991–996. [PMC free article] [PubMed]
16. Merchant SS, Prochnik SE, Vallon O, Harris EH, Karpowicz SJ, Witman GB, Terry A, Salamov A, Fritz-Laylin LK, Marechal-Drouard L, et al. The Chlamydomonas genome reveals the evolution of key animal and plant functions. Science. 2007;318:245–250. [PMC free article] [PubMed]
17. Schmutz J, Cannon SB, Schlueter J, Ma J, Mitros T, Nelson W, Hyten DL, Song Q, Thelen JJ, Cheng J, et al. Genome sequence of the palaeopolyploid soybean. Nature. 2010;463:178–183. [PubMed]
18. Ouyang S, Zhu W, Hamilton J, Lin H, Campbell M, Childs K, Thibaud-Nissen F, Malek RL, Lee Y, Zheng L, et al. The TIGR rice genome annotation resource: improvements and new features. Nucleic Acids Res. 2007;35:D883–D887. [PMC free article] [PubMed]
19. Rensing SA, Lang D, Zimmer AD, Terry A, Salamov A, Shapiro H, Nishiyama T, Perroud PF, Lindquist EA, Kamisugi Y, et al. The Physcomitrella genome reveals evolutionary insights into the conquest of land by plants. Science. 2008;319:64–69. [PubMed]
20. Tuskan GA, Difazio S, Jansson S, Bohlmann J, Grigoriev I, Hellsten U, Putnam N, Ralph S, Rombauts S, Salamov A, et al. The genome of black cottonwood, Populus trichocarpa (Torr. & Gray) Science. 2006;313:1596–1604. [PubMed]
21. Banks JA, Nishiyama T, Hasebe M, Bowman JL, Gribskov M, dePamphilis C, Albert VA, Aono N, Aoyama T, Ambrose BA, et al. The Selaginella genome identifies genetic changes associated with the evolution of vascular plants. Science. 2011;332:960–963. [PMC free article] [PubMed]
22. Paterson AH, Bowers JE, Bruggmann R, Dubchak I, Grimwood J, Gundlach H, Haberer G, Hellsten U, Mitros T, Poliakov A, et al. The Sorghum bicolor genome and the diversification of grasses. Nature. 2009;457:551–556. [PubMed]
23. Jaillon O, Aury JM, Noel B, Policriti A, Clepet C, Casagrande A, Choisne N, Aubourg S, Vitulo N, Jubin C, et al. The grapevine genome sequence suggests ancestral hexaploidization in major angiosperm phyla. Nature. 2007;449:463–467. [PubMed]
24. Prochnik SE, Umen J, Nedelcu AM, Hallmann A, Miller SM, Nishii I, Ferris P, Kuo A, Mitros T, Fritz-Laylin LK, et al. Genomic analysis of organismal complexity in the multicellular green alga Volvox carteri. Science. 2010;329:223–226. [PMC free article] [PubMed]
25. Schnable PS, Ware D, Fulton RS, Stein JC, Wei F, Pasternak S, Liang C, Zhang J, Fulton L, Graves TA, et al. The B73 maize genome: complexity, diversity, and dynamics. Science. 2009;326:1112–1115. [PubMed]
26. Finn RD, Mistry J, Tate J, Coggill P, Heger A, Pollington JE, Gavin OL, Gunasekaran P, Ceric G, Forslund K, et al. The Pfam protein families database. Nucleic Acids Res. 2010;38:D211–D222. [PMC free article] [PubMed]
27. Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28:27–30. [PMC free article] [PubMed]
28. Koonin EV, Fedorova ND, Jackson JD, Jacobs AR, Krylov DM, Makarova KS, Mazumder R, Mekhedov SL, Nikolskaya AN, Rao BS, et al. A comprehensive evolutionary classification of proteins encoded in complete eukaryotic genomes. Genome Biol. 2004;5:R7. [PMC free article] [PubMed]
29. Mi H, Guo N, Kejariwal A, Thomas PD. PANTHER version 6: protein sequence and function evolution data with expanded representation of biological pathways. Nucleic Acids Res. 2007;35:D247–D252. [PMC free article] [PubMed]
30. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 2000;25:25–29. [PMC free article] [PubMed]
31. Hunter S, Apweiler R, Attwood TK, Bairoch A, Bateman A, Binns D, Bork P, Das U, Daugherty L, Duquenne L, et al. InterPro: the integrative protein signature database. Nucleic Acids Res. 2009;37:D211–D215. [PMC free article] [PubMed]
32. Frazer KA, Pachter L, Poliakov A, Rubin EM, Dubchak I. VISTA: computational tools for comparative genomics. Nucleic Acids Res. 2004;32:W273–W279. [PMC free article] [PubMed]
33. Hartmann S, Lu D, Phillips J, Vision TJ. Phytome: a platform for plant comparative genomics. Nucleic Acids Res. 2006;34:D724–D730. [PMC free article] [PubMed]
34. Wall PK, Leebens-Mack J, Muller KF, Field D, Altman NS, dePamphilis CW. PlantTribes: a gene and gene family resource for comparative genomics in plants. Nucleic Acids Res. 2008;36:D970–D976. [PMC free article] [PubMed]
35. Remm M, Storm CE, Sonnhammer EL. Automatic clustering of orthologs and in-paralogs from pairwise species comparisons. J. Mol. Biol. 2001;314:1041–1052. [PubMed]
36. Li L, Stoeckert CJ, Jr, Roos DS. OrthoMCL: identification of ortholog groups for eukaryotic genomes. Genome Res. 2003;13:2178–2189. [PMC free article] [PubMed]
37. Chiu JC, Lee EK, Egan MG, Sarkar IN, Coruzzi GM, DeSalle R. OrthologID: automation of genome-scale ortholog identification within a parsimony framework. Bioinformatics. 2006;22:699–707. [PubMed]
38. Ruan J, Li H, Chen Z, Coghlan A, Coin LJ, Guo Y, Heriche JK, Hu Y, Kristiansen K, Li R, et al. TreeFam: 2008 Update. Nucleic Acids Res. 2008;36:D735–D740. [PMC free article] [PubMed]
39. Tatusov RL, Koonin EV, Lipman DJ. A genomic perspective on protein families. Science. 1997;278:631–637. [PubMed]
40. Rasmussen MD, Kellis M. Accurate gene-tree reconstruction by learning gene- and species-specific substitution rates across multiple complete genomes. Genome Res. 2007;17:1932–1942. [PMC free article] [PubMed]
41. Lynch M. The frailty of adaptive hypotheses for the origins of organismal complexity. Proc. Natl Acad. Sci. USA. 2007;104(Suppl. 1):8597–8604. [PMC free article] [PubMed]
42. Ohno S, Wolf U, Atkin NB. Evolution from fish to mammals by gene duplication. Hereditas. 1968;59:169–187. [PubMed]
43. Dehal PS, Boore JL. A phylogenomic gene cluster resource: the Phylogenetically Inferred Groups (PhIGs) database. BMC Bioinformatics. 2006;7:201. [PMC free article] [PubMed]
44. Butler G, Rasmussen MD, Lin MF, Santos MA, Sakthikumar S, Munro CA, Rheinbay E, Grabherr M, Forche A, Reedy JL, et al. Evolution of pathogenicity and sexual reproduction in eight Candida genomes. Nature. 2009;459:657–662. [PMC free article] [PubMed]
45. Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32:1792–1797. [PMC free article] [PubMed]
46. Eddy SR. A new generation of homology search tools based on probabilistic inference. Genome Inform. 2009;23:205–211. [PubMed]
47. Smith TF, Waterman MS. Identification of common molecular subsequences. J. Mol. Biol. 1981;147:195–197. [PubMed]
48. Stajich JE, Block D, Boulez K, Brenner SE, Chervitz SA, Dagdigian C, Fuellen G, Gilbert JG, Korf I, Lapp H, et al. The Bioperl toolkit: Perl modules for the life sciences. Genome Res. 2002;12:1611–1618. [PMC free article] [PubMed]
49. Velasco R, Zharkikh A, Affourtit J, Dhingra A, Cestaro A, Kalyanaraman A, Fontana P, Bhatnagar SK, Troggio M, Pruss D, et al. The genome of the domesticated apple (Malus x domestica Borkh.) Nat. Genet. 2010;42:833–839. [PubMed]
50. Shulaev V, Sargent DJ, Crowhurst RN, Mockler TC, Folkerts O, Delcher AL, Jaiswal P, Mockaitis K, Liston A, Mane SP, et al. The genome of woodland strawberry (Fragaria vesca) Nat. Genet. 2011;43:109–116. [PMC free article] [PubMed]
51. Xu X, Pan S, Cheng S, Zhang B, Mu D, Ni P, Zhang G, Yang S, Li R, Wang J, et al. Genome sequence and analysis of the tuber crop potato. Nature. 2011;475:189–195. [PubMed]
52. Smit, A.H., R; Green, P. (1996–2010)
53. Smit, A.H., R; Green, P. (2008–2010)
54. Haas BJ, Delcher AL, Mount SM, Wortman JR, Smith RK, Jr, Hannick LI, Maiti R, Ronning CM, Rusch DB, Town CD, et al. Improving the Arabidopsis genome annotation using maximal transcript alignment assemblies. Nucleic Acids Res. 2003;31:5654–5666. [PMC free article] [PubMed]
55. Slater GS, Birney E. Automated generation of heuristics for biological sequence comparison. BMC Bioinformatics. 2005;6:31. [PMC free article] [PubMed]
56. Yeh RF, Lim LP, Burge CB. Computational inference of homologous gene structures in the human genome. Genome Res. 2001;11:803–816. [PMC free article] [PubMed]
57. Salamov AA, Solovyev VV. Ab initio gene finding in Drosophila genomic DNA. Genome Res. 2000;10:516–522. [PMC free article] [PubMed]

Articles from Nucleic Acids Research are provided here courtesy of Oxford University Press
PubReader format: click here to try

Formats:

Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...

Links

  • PubMed
    PubMed
    PubMed citations for these articles

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...