A database of Orthologous Mammalian Markers

Description :

The EnsEMBL and NCBI databases were used to decide on a set of 1-to-1 orthologous markers from those mammalian genomes available. Exons of reasonable length for further amplification from genomic DNA and sequencing in additional species were then selected. For phylogenomic purposes, CoDing Sequences (CDSs) were also collected. The phylogenetic utility and the evolutionary characteristics of these candidate markers were then evaluated using a homemade bioinformatics pipeline. The resulting OrthoMaM database can be interrogated through this website.


[Warning: In this v10b version, we detected 163 markers for which alignment filtering disrupted the reading frame. This have been corrected on 27th April 2020 (see Release v10c)]

116

Species

14509

CDS markers

6888

Exons Markers

110

Works that cited OrthoMaM

If you use OrthoMam, please cite one of these references:

The following works cited OrthoMaM MBE (2014) :

The following works cited OrthoMaM BMC (2007) :

  • 79. Stronger selective constraint on downstream genes in the oxidative phosphorylation pathway of cetaceans. R. Tian, S. Xu, S. Chai, D. Yin, H. Zakon and G. Yang. Journal of Evolutionary Biology 31: 217-228, 2018.
  • 78. Divergent selection of pattern recognition receptors in mammals with different ecological characteristics. R. Tian, M. X. Chen, S. M. Chai, X. H. Rong, B. Y. Chen, W. H. Ren, S. X. Xu and G. Yang. Journal of Molecular Evolution 86: 138-149, 2018.
  • 77. On the importance of homology in the age of phylogenomics. M. S. Springer and J. Gatesy. Systematics and Biodiversity 16: 210-228, 2018.
  • 76. Pinniped diphyly and bat triphyly: More homology errors drive conflicts in the mammalian tree. M. S. Springer and J. Gatesy. Journal of Heredity 109: 297-307, 2018.
  • 75. Hologenomic adaptations underlying the evolution of sanguivory in the common vampire bat. M. L. Z. Mendoza, Z. J. Xiong, M. Escalera-Zamudio, A. K. Runge, J. Theze, D. Streicker, H. K. Frank, E. Loza-Rubio, S. M. Liu, O. A. Ryder, J. A. S. Castruita, A. Katzourakis, G. Pacheco, B. Taboada, U. Lober, O. G. Pybus, Y. Li, E. Rojas-Anaya, K. Bohmann, A. C. Baez, C. F. Arias, S. P. Liu, A. D. Greenwood, M. F. Bertelsen, N. E. White, M. Bunce, G. J. Zhang, T. Sicheritz-Ponten and M. P. T. Gilbert. Nature Ecology & Evolution 2: 659-668, 2018.
  • 74. The pace 2017 parameterized algorithms and computational experiments challenge: The second iteration. H. Dell, C. Komusiewicz, N. Talmon and M. Weller. , 2017.
  • 73. Uncertainty in phylogenetic tree estimates. A. Willis and R. Bell. , 2017.
  • 72. Macrosystematics of eutherian mammals combining HTS data to expand taxon coverage. M. Feijoo and A. Parada. Molecular Phylogenetics and Evolution 113: 76-83, 2017.
  • 71. Mitogenomic phylogeny, diversification, and biogeography of South American spiny rats. P.-H. Fabre, N. S. Upham, L. H. Emmons, F. Justy, Y. L. R. Leite, A. C. Loss, L. Orlando, M. Tilak, B. D. Patterson and E. J. P. Douzery. , 2017.
  • 70. A tree of geese: A phylogenomic perspective on the evolutionary history of true geese. J. Ottenburghs, H. J. Megens, R. H. S. Kraus, O. Madsen, P. van Hooft, S. E. van Wieren, R. P. M. A. Crooijmans, R. C. Ydenberg, M. A. M. Groenen and H. H. T. Prins. Molecular Phylogenetics and Evolution 101: 303-313, 2016.
  • 69. Implementing and testing the multispecies coalescent model: A valuable paradigm for phylogenomics. S. V. Edwards, Z. X. Xi, A. Janke, B. C. Faircloth, J. E. McCormack, T. C. Glenn, B. J. Zhong, S. Y. Wu, E. M. Lemmon, A. R. Lemmon, A. D. Leache, L. Liu and C. C. Davis. Molecular Phylogenetics and Evolution 94: 447-462, 2016.
  • 68. Identification and qualification of 500 nuclear, single-copy, orthologous genes for the Eupulmonata (Gastropoda) using transcriptome sequencing and exon capture. L. C. Teasdale, F. Köhler, K. D. Murray, T. O'Hara and A. Moussalli. Molecular Ecology Resources 16: 1107-1123, 2016.
  • 67. The gene tree delusion. M. S. Springer and J. Gatesy. Molecular Phylogenetics and Evolution 94: 1-33, 2016.
  • 66. Evolutionary genetics of hypoxia tolerance in cetaceans during diving. R. Tian, Z. F. Wang, X. Niu, K. Y. Zhou, S. X. Xu and G. Yang. Genome Biology and Evolution 8: 827-839, 2016.
  • 65. Evolution of digestive enzymes and RNASE1 provides insights into dietary switch of cetaceans. Z. F. Wang, S. X. Xu, K. X. Du, F. Huang, Z. Chen, K. Y. Zhou, W. H. Ren and G. Yang. Molecular Biology and Evolution 33: 3144-3157, 2016.
  • 64. The position of tree shrews in the mammalian tree: Comparing multi-gene analyses with phylogenomic results leaves monophyly of Euarchonta doubtful. X. M. Zhou, F. M. Sun, S. X. Xu, G. Yang and M. Li. Integrative Zoology 10: 186-198, 2015.
  • 63. Optimization of sequence alignments according to the number of sequences vs. number of sites trade-off. J. Y. Dutheil and E. Figuet. Bmc Bioinformatics 16: 2015.
  • 62. 'Obesity' is healthy for cetaceans? Evidence from pervasive positive selection in genes related to triacylglycerol metabolism. Z. F. Wang, Z. Chen, S. X. Xu, W. H. Ren, K. Y. Zhou and G. Yang. Scientific Reports 5: 1-12, 2015.
  • 61. Conservation of pro-longevity genes among mammals. C. M. Lindborg, K. J. Propert and R. J. Pignolo. Mechanisms of Ageing and Development 146: 23-27, 2015.
  • 60. Naked but not hairless: the pitfalls of analyses of molecular adaptation based on few genome sequence comparisons. F. Delsuc and M. K. Tilak. Genome Biol. Evol. 7: 768-774, 2015.
  • 59. GUIDANCE2: accurate detection of unreliable alignment regions accounting for the uncertainty of multiple parameters. I. Sela, H. Ashkenazy, K. Katoh and T. Pupko. Nucleic Acids Research 43: W7-W14, 2015.
  • 58. A targeted next-generation sequencing toolkit for exon-based cichlid phylogenomics. K. L. Ilves and H. Lopez-Fernandez. Mol. Ecol. Resour. 14: 802-11, 2014.
  • 57. Practical performance of tree comparison metrics. M. K. Kuhner and J. Yamato. Syst. Biol. 64: 205-14, 2014.
  • 56. Population genomics of eusocial insects: the costs of a vertebrate-like effective population size. J. Romiguier, J. Lourenco, P. Gayral, N. Faivre, L. A. Weinert, S. Ravel, M. Ballenghien, V. Cahais, A. Bernard, E. Loire, L. Keller and N. Galtier. J. Evol. Biol. 27: 593-603, 2014.
  • 55. Phylostratigraphic bias creates spurious patterns of genome evolution. B. A. Moyers and J. Zhang. Mol. Biol. Evol. 32: 258-67, 2014.
  • 54. Phylogenetic analysis at deep timescales: unreliable gene trees, bypassed hidden support, and the coalescence/concatalescence conundrum. J. Gatesy and M. S. Springer. Mol. Phylogenet. Evol. 80: 231-66, 2014.
  • 53. Performance of genomic data sets on the estimation of the divergence time of New World and Old World anthropoids. C. G. Schrago and C. M. Voloch. Genet. Mol. Res. 13: 1425-37, 2014.
  • 52. Monte Carlo algorithms for Brownian phylogenetic models. B. Horvilleur and N. Lartillot. Bioinformatics 30: 3020-8, 2014.
  • 51. Indel reliability in indel-based phylogenetic inference. H. Ashkenazy, O. Cohen, T. Pupko and D. Huchon. Genome Biol. Evol. 6: 3199-209, 2014.
  • 50. How low can you go? The effects of mutation rate on the accuracy of species-tree estimation. H. C. Lanier, H. Huang and L. L. Knowles. Mol. Phylogenet. Evol. 70: 112-9, 2014.
  • 49. Eyes underground: regression of visual protein networks in subterranean mammals. C. A. Emerling and M. S. Springer. Mol. Phylogenet. Evol. 78: 260-70, 2014.
  • 48. Development of rapidly evolving intron markers to estimate multilocus species trees of rodents. A. Rodriguez-Prieto, J. Igea and J. Castresana. PLoS One 9: e96032, 2014.
  • 47. Assignment of Calibration Information to Deeper Phylogenetic Nodes is More Effective in Obtaining Precise and Accurate Divergence Time Estimates. B. Mello and C. G. Schrago. Evol. Bioinform. Online 10: 79-85, 2014.
  • 46. Alignment errors strongly impact likelihood-based tests for comparing topologies. E. L. Karin, E. Susko and T. Pupko. Mol. Biol. Evol. 31: 3057-3067, 2014.
  • 45. Next-generation sequencing and phylogenetic signal of complete mitochondrial genomes for resolving the evolutionary history of leaf-nosed bats (Phyllostomidae). F. Botero-Castro, M. K. Tilak, F. Justy, F. Catzeflis, F. Delsuc and E. J. Douzery. Mol. Phylogenet. Evol. 69: 728-39, 2013.
  • 44. Genome-wide signatures of convergent evolution in echolocating mammals. J. Parker, G. Tsagkogeorga, J. A. Cotton, Y. Liu, P. Provero, E. Stupka and S. J. Rossiter. Nature 502: 228-31, 2013.
  • 43. Evaluating phylogenetic informativeness as a predictor of phylogenetic signal for metazoan, fungal, and mammalian phylogenomic data sets. F. Lopez-Giraldez, A. H. Moeller and J. P. Townsend. Biomed Res. Int. 2013: 621604, 2013.
  • 42. Adaptive evolution of the osmoregulation-related genes in cetaceans during secondary aquatic adaptation. S. Xu, Y. Yang, X. Zhou, J. Xu, K. Zhou and G. Yang. BMC Evol. Biol. 13: 189, 2013.
  • 41. Novel algorithm for phylogenetic analysis of proteins: application to analysis of the evolution of H5N1 influenza viruses. V. R. Perovic. J. Math. Chem. 51: 2238-2255, 2013.
  • 40. Less is more in mammalian phylogenomics: AT-rich genes minimize tree conflicts and unravel the root of placental mammals. J. Romiguier, V. Ranwez, F. Delsuc, N. Galtier and E. J. P. Douzery. Mol. Biol. Evol. 30: 2134-2144, 2013.
  • 39. Evolution of functional genes in cetaceans driven by natural selection on a phylogenetic and population level. A. E. Moura, A. Natoli, E. Rogan and A. R. Hoelzel. Evol. Biol. 40: 341-354, 2013.
  • 38. Efficient newly designed primers for the amplification and sequencing of bird mitochondrial genomes. S. A. Amer, M. M. Ahmed and M. Shobrak. Biosci. Biotechnol. Biochem. 77: 577-581, 2013.
  • 37. Conventional simulation of biological sequences leads to a biased assessment of multi-loci phylogenetic analysis. B. O. Aguiar and C. G. Schrago. Evol. Bioinformatics 9: 317-325, 2013.
  • 36. The precision of the hominid timescale estimated by relaxed clock methods. C. G. Schrago and C. M. Voloch. J. Evol. Biol. 26: 746-755, 2013.
  • 35. Bayesian selection of nucleotide substitution models and their site assignments. C.-H. Wu, M. A. Suchard and A. J. Drummond. Mol. Biol. Evol. 30: 669-688, 2013.
  • 34. Phylogenetic patterns of GC-biased gene conversion in placental mammals and the evolutionary dynamics of recombination landscapes. N. Lartillot. Mol. Biol. Evol. 30: 489-502, 2013.
  • 33. High levels of gene expression explain the strong evolutionary constraint of mitochondrial protein-coding genes. B. Nabholz, H. Ellegren and J. B. W. Wolf. Mol. Biol. Evol. 30: 272-284, 2013.
  • 32. Genomic evidence for large, long-lived ancestors to placental mammals. J. Romiguier, V. Ranwez, E. J. P. Douzery and N. Galtier. Mol. Biol. Evol. 30: 5-13, 2013.
  • 31. Combining multiple autosomal introns for studying shallow phylogeny and taxonomy of Laurasiatherian mammals: Application to the tribe Bovini (Cetartiodactyla, Bovidae). A. Hassanin, J. An, A. Ropiquet, T. T. Nguyen and A. Couloux. Mol. Phylogenet. Evol. 66: 766-775, 2013.
  • 30. E value cutoff and eukaryotic genome content phylogenetics. J. A. Rosenfeld and R. DeSalle. Mol. Phylogenet. Evol 63: 342-350, 2012.
  • 29. EvolMarkers: a database for mining exon and intron markers for evolution, ecology and conservation studies. C. Li, J.-J. M. Riethoven and G. J. P. Naylor. Mol. Ecol. Res. 12: 967-971, 2012.
  • 28. A method to find longevity-selected positions in the mammalian proteome. J. Semeiks and N. V. Grishin. PLoS One 7: e38595, 2012.
  • 27. ALG11 — a new variable DNA marker for sponge phylogeny: comparison of phylogenetic performances with the 18S rDNA and the COI gene. F. Belinky, A. Szitenberg, I. Goldfarb, T. Feldstein, G. Wörheide, M. Ilan and D. Huchon. Mol. Phylogenet. Evol. 63: 702-713, 2012.
  • 26. Impact of the partitioning scheme on divergence times inferred from mammalian genomic data sets. C. M. Voloch and C. G. Schrago. Evol. Bioinformatics 8: 207-218, 2012.
  • 25. Fast and robust characterization of time-heterogeneous sequence evolutionary processes using substitution mapping. J. Romiguier, E. Figuet, N. Galtier, E. J. P. Douzery, B. Boussau, J. Y. Dutheil and V. Ranwez. PLoS One 7: e33852, 2012.
  • 24. Comprehensive primer design for analysis of population genetics in non-sequenced organisms. A. Tezuka, N. Matsushima, Y. Nemoto, H. D. Akashi, M. Kawata and T. Makino. PLoS ONE 7: e32314, 2012.
  • 23. Evolutionary and functional analyses of the interaction between the myeloid restriction factor SAMHD1 and the lentiviral Vpx protein. N. Laguette, N. Rahm, B. Sobhian, C. Chable-Bessia, J. Münch, J. Snoeck, D. Sauter, W. M. Switzer, W. Heneine, F. Kirchhoff, F. Delsuc, A. Telenti and M. Benkirane. Cell Host Microbe 11: 205-217, 2012.
  • 22. Testing synchrony in historical biogeography: the case of New World primates and Hystricognathi rodents. L. Loss-Oliveira, B. O. Aguiar and C. Schrago. Evol. Bioinformatics 8: 127–137, 2012.
  • 21. Model averaging and Bayes factor calculation of relaxed molecular clocks in Bayesian phylogenetics. W. L. S. Li and A. J. Drummond. Mol. Biol. Evol. 29: 751-761, 2012.
  • 20. Phylogenomic analysis resolves the interordinal relationships and rapid diversification of the Laurasiatherian mammals. X. Zhou, S. Xu, J. Xu, B. Chen, K. Zhou and G. Yang. Syst. Biol. 61: 150-164, 2012.
  • 19. MACSE: Multiple Alignment of Coding SEequences accounting for frameshifts and stop codons. V. Ranwez, S. Harispe, F. Delsuc and E. J. P. Douzery. PLoS ONE 6: e22594, 2011.
  • 18. PhyDesign: an online application for profiling phylogenetic informativeness. F. López-Giráldez and J. P. Townsend. BMC Evol. Biol. 11: 152, 2011.
  • 17. Phylogenomic analyses and improved resolution of Cetartiodactyla. X. Zhou, S. Xu, Y. Yang, K. Zhou and G. Yang. Mol. Phylogenet. Evol. 61: 255-264, 2011.
  • 16. Morphology, molecular phylogeny, and taxonomic inconsistencies in the study of Bradypus sloths (Pilosa: Bradypodidae). N. de Moraes-Barros, J. A. B. Silva and J. S. Morgante. J. Mammal. 92: 86-100, 2011.
  • 15. Developing a series of conservative anchor markers and their application to phylogenomics of Laurasiatherian mammals. X. Zhou, S. Xu, P. Zhang and G. Yang. Mol. Ecol. Resources 11: 134-140, 2011.
  • 14. Protein structural modularity and robustness are associated with evolvability M. M. Rorick and G. P. Wagner. Genome Biol. Evol. 3: 456-475, 2011.
  • 13. Novel intron markers to study the phylogeny of closely related mammalian species. J. Igea, J. Juste and J. Castresana. BMC Evol. Biol. 10: 369, 2010.
  • 12. Analyzing the relationship between sequence divergence and nodal support using Bayesian phylogenetic analyses. R. Makowsky, C. L. Cox, C. Roelke and P. T. Chippindale. Mol. Phylogenet. Evol. 57: 485-494, 2010.
  • 11. Contrasting GC-content dynamics across 33 mammalian genomes: relationship with life-history traits and chromosome sizes. J. Romiguier, V. Ranwez, E. J. P. Douzery and N. Galtier. Genome Res. 20: 1001-1009, 2010.
  • 10. SuperTriplets: A triplet-based supertree approach to molecular systematics and phylogenomics. V. Ranwez, A. Criscuolo and E. J. P. Douzery. Bioinformatics 26: i115-i123, 2010.
  • 09. An evolutionary genome scan for longevity-related natural selection in mammals. R. W. Jobson, B. Nabholz and N. Galtier. Mol. Biol. Evol. 27: 840-847, 2010.
  • 08. The expansion of amino-acid repeats is not associated to adaptive evolution in mammalian genes. F. Cruz, J. Roux and M. Robinson-Rechavi. BMC Genomics 10: 619, 2009.
  • 07. Covariation of branch lengths in phylogenies of functionally related genes. W. L. S. Li and A. G. Rodrigo. PLoS ONE 4: e8487, 2009.
  • 06. Computer-assisted automatic classifications, storage, queries and functional assignments of orthologs and in-paralogs proteins. D. Thybert, S. Avner, C. Lucchetti-Miganeh and F. Barloy-Hubler. Curr. Bioinformatics 4: 129-140, 2009.
  • 05. PhyloExplorer: a web server to validate, explore and query phylogenetic trees. V. Ranwez, N. Clairon, F. Delsuc, S. Pourali, N. Auberval, S. Diser and V. Berry. BMC Evol. Biol. 9: 108, 2009.
  • 04. Reviews in comparative genomic research based on orthologs. Z.-X. Pan, D. Xu, J.-B. Zhang, F. Lin, B.-J. Wu and H.-L. Liu. Hereditas (Beijing) 31: 457-463, 2009.
  • 03. GC-biased gene conversion promotes the fixation of deleterious amino acid changes in primates. N. Galtier, L. Duret, S. Glémin and V. Ranwez. Trends Genet. 25: 1-5, 2009.
  • 02. IDEA: Interactive Display for Evolutionary Analyses. A. Egan, A. Mahurkar, J. Crabtree, J. H. Badger, J. M. Carlton and J. C. Silva. BMC Bioinformatics 9: 524, 2008.
  • 01. PhySIC_IST: cleaning source trees to infer more informative supertrees. C. Scornavacca, V. Berry, V. Lefort, E. J. P. Douzery and V. Ranwez. BMC BioInformatics 9: 413, 2008.

Word cloud of papers abstracts that have used and cited OrthoMaM:







A database of Orthologous Mammalian Markers

Parameters

Expected number of markers * :







To delete an element in inputs fields, select it and use the 'suppr' button.





Results

For details on a marker, click on the green button in the query result table.
For accurate filtering, you can adjust the bounds in the purple frame. Example for %GC3: 30.0 ... 40.0



Download


ruuning
Nucleotide and Amino Acid : Filtered with HMMCleaner and MACSE



You can also dowload all archives for CDS or Exons






A database of Orthologous Mammalian Markers

Params


Results

Download








A database of Orthologous Mammalian Markers

Database Summary

The utility of a phylogenetic marker can be described by its relative evolutionary rate (RER): faster (respectively slower) evolving markers will be more suitable for lower (respectively deeper) taxonomic levels.

In a first approximation, the total branch length (TBL) of the maximum likelihood (ML) tree is a reasonable descriptor of the evolutionary rate of a given exon / CDS. However, the TBL will preclude fair comparisons among different exons / CDS when the taxon sampling differs: the higher the species number, the longer the TBL.

To circumvent this problem, we use the Super Distance Matrix (SDM) approach [Criscuolo et al. 2006], with a three-step procedure:

  1. The ML tree inferred from each of the exons / CDS is converted into a matrix of additive distances by computing the path-length between each pair of species.
  2. Each of the matrices is brought closer to the others by a factor (αp), according to the least-squares criterion. This operation is equivalent to multiplying by αp every branch length of the initial trees.
  3. Optimal values of the alpha_p parameters are calculated following Criscuolo et al. (2006).
    As αp are inversely proportional to the evolutionary rates, 1/αp values provide a measure of rate heterogeneities among exons / CDS even if the number of taxa differs.
    Here, relative evolutionary rate SDM estimates range from 0.01 to 5 (OrthoMaM mean = 1.2 ; standard-error = 0.6). For example, if exons / CDSs X and Y are respectively characterized by relative rates rX = 0.2 and rY = 2.0, this means that Y is evolving 10 times faster than X.

Request guidelines: In the [0-5] range of values, type RER < 1 to query rather conserved markers, 1 < RER < 2 for more variable markers, and RER > 2 for fast-evolving ones.

Reference: SDM: a fast distance-based approach for (super)tree building in phylogenomics. Criscuolo A., Berry V., Douzery E. J. P. & Gascuel O. Systematic Biology 55 (5) : 740-755. 2006.

The substitution rate heterogeneity among sites of the exon / CDS alignment is described by the Γ distribution.

Lower (respectively higher) α values correspond to strong (respectively weak) heterogeneity. If α > 1, the substitution pattern among sites is rather homogeneous.

Request guidelines: In the [0-5] range of values, type alpha < 1 to query markers with stronger among-sites variability, and alpha > 1 for alignments with more evenly distributed variability.

Reference: Among-site rate variation and its impact on phylogenetic analyses. Yang Z. Trends in Ecology and Evolution 11 (9) : 367-372. 1996.

The percentage of G+C on third codon positions is a descriptor of the degree of base composition heterogeneity.

G+C content is more contrasted on third codon positions than on the whole exon / CDS.

Request guidelines:
In the [20-95] range of values, type %GC3 < 40 to query A+T rich markers,
40 < %GC3 < 60 for more equilibrated markers, and %GC3 > 60 for G+C rich markers.







A database of Orthologous Mammalian Markers

Release v10c , April 2020 (current version).
  • Correction of codon and amino acid alignments (CDSs and exons) for 163 markers for which alignment filtering disrupted the reading frame.
  • Phylogenetic trees were not affected but evolutionary parameters (site variability and GC3) have been updated.
  • The list of affected markers and corrected aligments can be found here : CDSs & exons.
  • If you downloaded data for one of these markers since October 2018 please update your data. We sincerely apologize for the inconvenience.
  • Note that 14 selenoproteins with an alternative genetic code (TGA => O instead of stop) that has not been taken into account are included in OMM v10. The list of affected markers can be found here : CDSs & exons.
Release v10b, October 2018.
  • Requests on 116 species (based on EnsEMBL v91, December 2017, and NCBI, March 2018).
Release v10a, February 2018
  • Requests on 92 species (based on EnsEMBL v88, March 2017, and NCBI, March 2017).
  • Major website redesign.
Release v9, April 2015
  • Requests on 43 species (based on EnsEMBL v79, March 2015).
  • New species: Papio_anubis, Chlorocebus_sabaeus, Ovis_aries.
  • Exon detection has been improved.
  • Raw alignements have been computed with MAFFT.
  • In this release, we did not exclude alignments which contain sequences leading to very high branch lengths in the corresponding ML phylograms.
Release v8, October 2013
  • Requests on 40 species (based on EnsEMBL v73, September 2013).
  • New species: Mustela_putorius_furo.
Release v7, February 2012
  • Requests on 39 species (based on EnsEMBL v65, December 2011).
  • New species: Nomascus_leucogenys, Ailuropoda_melanoleuca, Sarcophilus_harrisii.
  • Sequence alignments have been improved and now rely on MACSE to detect potential frameshifts.
  • As a consequence alignments may contain the "!" that indicates frameshift events. You can safely replace them by "-" in DNA alignments or by "X" in protein alignments.
  • Unreliable alignment sites/sequences are removed using trimAl before phylogenetic analyses (raw and filtered alignments are provided).
  • Exon orthology prediction has been improved and is now based on the corresponding CDS alignments.
  • Marker detail rendering is now compatible with most web browsers: Firefox, IE, Safari, Chrome (thanks to Benjamin Robert).
  • A visual rendering of GO annotation is available based on OntoFocus (thanks to Sebastien Harispe).
Release v6, September 2010
  • Data are the same as in v6a but web interface is improved
  • There are now two ways to access markers:
    • the former textual query form
    • a simpler visual way to browse markers
  • Query results appear in different windows so that query criteria are not lost.
  • Markers can be queried using any EnsEMBL gene ID (instead of just human ones).
  • Left menu is simplified (other minor human-computer interaction improvements have been done).
v6a, July 2010
  • Requests on 36 species (based on EnsEMBL v56, September 2009).
  • New species: Callithrix_jacchus, Sus_scrofa, Macropus_eugenii.
  • Queries can now be done using a list of human gene EnsEMBL identifiers (or gene symbols).
  • Maximum likelihood (ML) trees can be downloaded.
  • Thousands of files can now be downloaded at once instead of 100 in previous versions.
  • A bug about GO annotation rendering has been fixed.
Release v5, October 2009
  • Requests on 33 species (based on EnsEMBL v54, May 2009).
  • New species: Gorilla_gorilla, Tarsius_syrichta, Dipodomys_ordii, Vicugna_pacos, Tursiops_truncatus, Pteropus_vampyrus, Procavia_capensis, Choloepus_hoffmanni.
  • Exons / CDS can be queried according to a list of species required.
  • Markers can be queried based on the corresponding human gene EnsEMBL identifier.
  • Gene annotations are now available for each marker (human gene description and gene ontology [GO] terms).
  • Phylogenetic trees readability is enhanced by taxonomic coloring.
Release v4, July 2008
  • Requests on 25 taxa (based on EnsEMBL v49, March 2008)
  • This version includes both CDS and exon data.
  • Query results can now be sorted according to descriptors and downloaded as zip archives.
  • The average responsivness of the web server has been significantly improved.
Release v3, May 2008
  • Requests on 25 taxa (based on EnsEMBL v49, March 2008)
  • New species: Pongo_pygmaeus, Equus_caballus.
  • We found and corrected a bug in previous versions that, in very few alignments, led us to propose some non orthologous sequences.
Release v2, March 2008
  • Requests on 23 taxa (based on EnsEMBL v48, December 2007)
  • New species: Otolemur_garnettii, Microcebus_murinus, Tupaia_belangeri, Cavia_porcellus, Spermophilus_tridecemlineatus (= Ictidomys), Ochotona_princeps, Felis_catus, Myotis_lucifugus, Erinaceus_europaeus, Sorex_araneus, Ornithorhynchus_anatinus.
  • Amino acid alignments are provided.
  • A dedicated web server is used for this project.
  • Due to web connection trouble, some chromosomes were not completely analysed. Some markers were thus missing.
Release v1, July 2007
  • Requests on 12 taxa (based on EnsEMBL v41, October 2006)
  • Species list: Homo_sapiens, Pan_troglodytes, Macaca_mulatta, Mus_musculus, Rattus_norvegicus, Oryctolagus_cuniculus, Bos_taurus, Canis_familiaris, Dasypus_novemcinctus, Loxodonta_africana, Echinops_telfairi, Monodelphis_domestica.






A database of Orthologous Mammalian Markers

Parameters


Download



Results

Blast: Results

The query sequence(s) are added with mafft (--addfragments) to the existing marker alignment.
The resulting new alignment is then used to draw an NJ tree on pairwise distances using a JC69 model of DNA evolution.






A database of Orthologous Mammalian Markers

Help

The utility of a phylogenetic marker can be described by its relative evolutionary rate (RER): faster (respectively slower) evolving markers will be more suitable for lower (respectively deeper) taxonomic levels.

In a first approximation, the total branch length (TBL) of the maximum likelihood (ML) tree is a reasonable descriptor of the evolutionary rate of a given exon / CDS. However, the TBL will preclude fair comparisons among different exons / CDS when the taxon sampling differs: the higher the species number, the longer the TBL.

To circumvent this problem, we use the Super Distance Matrix (SDM) approach [Criscuolo et al. 2006], with a three-step procedure:

  1. The ML tree inferred from each of the exons / CDS is converted into a matrix of additive distances by computing the path-length between each pair of species.
  2. Each of the matrices is brought closer to the others by a factor (αp), according to the least-squares criterion. This operation is equivalent to multiplying by αp every branch length of the initial trees.
  3. Optimal values of the alpha_p parameters are calculated following Criscuolo et al. (2006).
    As αp are inversely proportional to the evolutionary rates, 1/αp values provide a measure of rate heterogeneities among exons / CDS even if the number of taxa differs.
    Here, relative evolutionary rate SDM estimates range from 0.01 to 5 (OrthoMaM mean = 1.2 ; standard-error = 0.6). For example, if exons / CDSs X and Y are respectively characterized by relative rates rX = 0.2 and rY = 2.0, this means that Y is evolving 10 times faster than X.

Request guidelines: In the [0-5] range of values, type RER < 1 to query rather conserved markers, 1 < RER < 2 for more variable markers, and RER > 2 for fast-evolving ones.

The substitution rate heterogeneity among sites of the exon / CDS alignment is described by the Γ distribution.

Lower (respectively higher) α values correspond to strong (respectively weak) heterogeneity. If α > 1, the substitution pattern among sites is rather homogeneous.

Request guidelines: In the [0-5] range of values, type alpha < 1 to query markers with stronger among-sites variability, and alpha > 1 for alignments with more evenly distributed variability.

The percentage of G+C on third codon positions is a descriptor of the degree of base composition heterogeneity.

G+C content is more contrasted on third codon positions than on the whole exon / CDS.

Request guidelines:
In the [20-95] range of values, type %GC3 < 40 to query A+T rich markers,
40 < %GC3 < 60 for more equilibrated markers, and %GC3 > 60 for G+C rich markers.