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Deliberately Unequal Gene Sampling, A Design of Molecular Studies Tested in Lepidoptera
Soowon Cho,Andreas Zwick,Jerome Regier,Charles Mitter,Michael Cummings,Jianxiu Yao,Zaile Du,Hong Zhao,Akito Kawahara,Susan Weller,Donald Davis,Joaquin Baixeras,John Brown,Cynthia Parr 한국응용곤충학회 2010 한국응용곤충학회 학술대회논문집 Vol.2010 No.05
Seeking to improve the weak resolution of deeper divergences in an initial study based on five nuclear genes (6.6kb total) in 123 exemplars, we nearly tripled the total sequence (to 26 genes, 18.4 kb total) in one third (41) of the taxa. The expanded, deliberately incomplete data matrix consistently increased bootstrap support for previously-identified groupings, while introducing no contradictory groupings of the kind that missing data have been predicted to produce. To test the relative effectiveness of “more genes” versus “more taxa” sind that we compared two largely complete matrices, the initial 5 gene × 123 taxon and the 26 gene × 41 taxon data sets, that contain roughly equal amounts of sequence. The “more genes” data set yielded consistently, sometimes dramatically higher bootstrap support that is generally not attributable to taxon number alone. We also found that a gene-rich taxon subset provides reassuring evidence of strong underlying signal that is not obvious in subsequent larger analyses, helping to encourage and guide the search for deep relationships amid the noise of expanded taxon sampling.