Should genes with missing data be excluded from phylogenetic analyses?

Molecular Phylogenetics and Evolution

Volumn 80, Issue , 2014, Pages 308-318

  Jiang, Wei ^a,b   Chen, Si Yun ^a   Wang, Hong ^a,b   Li, De Zhu ^a,b   Wiens, John J ^c  

^a KUNMING INSTITUTE OF BOTANY   (China)

^b UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^c The University of Arizona   (United States)

Author keywords

Accuracy; Maximum likelihood; Missing data; Phylogeny

Indexed keywords

BIOLOGICAL MODEL; CLASSIFICATION; CYTOLOGY; DNA SEQUENCE; GENETICS; PHYLOGENY; PROBABILITY; ROSALES; STATISTICAL ANALYSIS; STATISTICAL MODEL; YEAST;

DATA INTERPRETATION, STATISTICAL; LIKELIHOOD FUNCTIONS; MODELS, GENETIC; PHYLOGENY; PROBABILITY; ROSALES; SEQUENCE ANALYSIS, DNA; YEASTS;

EID: 84908448749     PISSN: 10557903     EISSN: 10959513     Source Type: Journal    
DOI: 10.1016/j.ympev.2014.08.006     Document Type: Article

References (42)

1. Akaike H. A new look at the statistical model identification. IEEE Trans. Aut. Control 1974, 19:716-723.
2. Burleigh J.G., Hilu K., Soltis D. Inferring phylogenies with incomplete data sets: a 5-gene, 567-taxon analysis of angiosperms. BMC Evol. Biol. 2009, 9:61.
3. Cho S., Zwick A., Regier J.C., Mitter C., Cummings M.P., Yao J., Du Z., Zhao H., Kawahara A.Y., Weller S. Can deliberately incomplete gene sample augmentation improve a phylogeny estimate for the advanced moths and butterflies (Hexapoda: Lepidoptera)?. Syst. Biol. 2011, 60:782-796.
4. Cranston K.A., Hurwitz B., Ware D., Stein L., Wing R.A. Species trees from highly incongruent gene trees in rice. Syst. Biol. 2009, 58:489-500.
5. de la Torre-Bárcena J.E., Kolokotronis S.-O., Lee E.K., Stevenson D.W., Brenner E.D., Katari M.S., Coruzzi G.M., DeSalle R. The impact of outgroup choice and missing data on major seed plant phylogenetics using genome-wide EST data. PLoS ONE 2009, 4:e5764.
6. Driskell A.C., Ané C., Burleigh J.G., McMahon M.M., O'Meara B.C., Sanderson M.J. Prospects for building the tree of life from large sequence databases. Science 2004, 306:1172-1174.
7. Drummond A.J., Ho S.Y.W., Phillips M.J., Rambaut A. Relaxed phylogenetics and dating with confidence. PLoS Biol. 2006, 4:e88.
8. Edwards S.V., Liu L., Pearl D.K. High-resolution species trees without concatenation. Proc. Natl. Acad. Sci. USA 2007, 104:5936-5941.
9. Felsenstein J. Inferring Phylogenies 2004, Sinauer Associates, Sunderland, MA.
10. Fulton T.L., Strobeck C. Molecular phylogeny of the Arctoidea (Carnivora): effect of missing data on supertree and supermatrix analyses of multiple gene data sets. Mol. Phylogenet. Evol. 2006, 41:165-181.
11. Heled J., Drummond A.J. Bayesian inference of species trees from multilocus data. Mol. Biol. Evol. 2010, 27:570-580.
12. Hovmöller R., Knowles L.L., Kubatko L.S. Effects of missing data on species tree estimation under the coalescent. Mol. Phylogenet. Evol. 2013, 69:1057-1062.
13. Huelsenbeck J.P. When are fossils better than extant taxa in phylogenetic analysis?. Syst. Biol. 1991, 40:458-469.
14. Lanfear R., Calcott B., Ho S.Y.W., Guindon S. PartitionFinder: combined selection of partitioning schemes and substitution models for phylogenetic analyses. Mol. Biol. Evol. 2012, 29:1695-1701.
15. Lemmon A.R., Brown J.M., Stanger-Hall K., Lemmon E.M. The effect of ambiguous data on phylogenetic estimates obtained by maximum likelihood and Bayesian inference. Syst. Biol. 2009, 58:130-145.
16. Philippe H., Snell E.A., Bapteste E., Lopez P., Holland P.W.H., Casane D. Phylogenomics of eukaryotes: impact of missing data on large alignments. Mol. Biol. Evol. 2004, 21:1740-1752.
17. Posada D., Buckley T.R. Model selection and model averaging in phylogenetics: advantages of Akaike Information Criterion and Bayesian approaches over likelihood ratio tests. Syst. Biol. 2004, 53:793-808.
18. Pyron, R.A., Burbrink, F.T., Colli, G.R., Nieto Montes de Oca, A., Vitt, L.J., Kuczynski, C.A., Wiens, J.J., 2011. The phylogeny of advanced snakes (Colubroidea), with discovery of a new subfamily and comparison of support methods for likelihood trees. Mol. Phylogenet. Evol. 58, 329-342.
19. Rokas A., Williams B.L., King N., Carroll S.B. Genome-scale approaches to resolving incongruence in molecular phylogenies. Nature 2003, 425:798-804.
20. Roure B., Baurain D., Philippe H. Impact of missing data on phylogenies inferred from empirical phylogenomic data sets. Mol. Biol. Evol. 2013, 30:197-214.
21. Rubin B.E.R., Ree R.H., Moreau C.S. Inferring phylogenies from RAD sequence data. PLoS ONE 2012, 7:e33394.
22. Sanderson M.J., McMahon M.M., Steel M. Phylogenomics with incomplete taxon coverage: the limits to inference. BMC Evol. Biol. 2010, 10:155.
23. Sanderson M.J., McMahon M.M., Steel M. Terraces in phylogenetic tree space. Science 2011, 333:448-450.
24. Schaefer H., Renner S.S. Phylogenetic relationships in the order Cucurbitales and a new classification of the gourd family (Cucurbitaceae). Taxon 2011, 60:122-138.
25. Soltis D.E., Smith S.A., Cellinese N., Wurdack K.J., Tank D.C., Brockington S.F., Refulio-Rodriguez N.F., Walker J.B., Moore M.J., Carlsward B.S., et al. Angiosperm phylogeny: 17 genes, 640 taxa. Am. J. Bot. 2011, 98:704-730.
26. Stamatakis A., Hoover P., Rougemont J. A rapid bootstrap algorithm for the RAxML Web servers. Syst. Biol. 2008, 57:758-771.
27. Stamatakis A. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics 2006, 22:2688-2690.
28. Sytsma K.J., Morawetz J., Pires J.C., Nepokroeff M., Conti E., Zjhra M., Hall J.C., Chase M.W. Urticalean rosids: circumscription, rosid ancestry, and phylogenetics based on rbcL, trnL-F, and ndhF sequences. Am. J. Bot. 2002, 89:1531-1546.
29. Wang H., Moore M., Soltis P., Bell C., Brockington S., Alexandre R., Davis C., Latvis M., Manchester S., Soltis D. Rosid radiation and the rapid rise of angiosperm-dominated forests. Proc. Natl. Acad. Sci. USA 2009, 106:3853-3858.
30. Wiens J.J., Moen D. Missing data and the accuracy of Bayesian phylogenetics. J. Syst. Evol. 2008, 46:307-314.
31. Wiens J.J., Morrill M.C. Missing data in phylogenetic analysis: reconciling results from simulations and empirical data. Syst. Biol. 2011, 60:719-731.
32. Wiens J.J., Reeder T.W. Combining data sets with different numbers of taxa for phylogenetic analysis. Syst. Biol. 1995, 44:548-558.
33. Wiens J.J., Tiu J. Highly incomplete taxa can rescue phylogenetic analyses from the negative impacts of limited taxon sampling. PLoS ONE 2012, 7:e42925.
34. Wiens J.J., Fetzner J.W., Parkinson C.L., Reeder T.W. Hylid frog phylogeny and sampling strategies for speciose clades. Syst. Biol. 2005, 54:778-807.
35. Wiens J.J., Kuczynski C.A., Smith S.A., Mulcahy D.G., Sites J.W., Townsend T.M., Reeder T.W. Branch lengths, support, and congruence: testing the phylogenomic approach with 20 nuclear loci in snakes. Syst. Biol. 2008, 57:420-431.
36. Wiens J.J., Kuczynski C.A., Townsend T., Reeder T.W., Mulcahy D.G., Sites J.W. Combining phylogenomics and fossils in higher-level squamate reptile phylogeny: molecular data change the placement of fossil taxa. Syst. Biol. 2010, 59:674-688.
37. Wiens J.J. Does adding characters with missing data increase or decrease phylogenetic accuracy?. Syst. Biol. 1998, 47:625-640.
38. Wiens J.J. Incomplete taxa, incomplete characters, and phylogenetic accuracy: is there a missing data problem?. J. Vertebr. Paleontol. 2003, 23:297-310.
39. Wiens J.J. Missing data, incomplete taxa, and phylogenetic accuracy. Syst. Biol. 2003, 52:528-538.
40. Wiens J.J. Can incomplete taxa rescue phylogenetic analyses from long-branch attraction?. Syst. Biol. 2005, 54:731-742.
41. Zhang S.D., Soltis D.E., Yang Y., Li D.Z., Yi T.S. Multi-gene analysis provides a well-supported phylogeny of Rosales. Mol. Phylogenet. Evol. 2011, 60:21-28.
42. Zwick A., Regier J.C., Mitter C., Cummings M.P. Increased gene sampling yields robust support for higher-level clades within Bombycoidea (Lepidoptera). Syst. Entomol. 2011, 36:31-43.