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Unforeseen Consequences of Excluding Missing Data from Next-Generation Sequences: Simulation Study of RAD Sequences.
Huateng Huang1, L Lacey Knowles2
1Department of Ecology and Evolutionary Biology, Museum of Zoology, University of Michigan, 1109 Geddes Avenue, Ann Arbor, MI 48109-1079, USA huatengh@umich.edu.
Systematic Biology
|July 6, 2014
Summary
Excluding missing data in next-generation sequencing (NGS) for phylogenetics can inadvertently remove informative loci with high mutation rates. This study shows that stringent missing data thresholds can bias phylogenetic and phylogeographic inferences.
Area of Science:
- Genomics
- Evolutionary Biology
- Bioinformatics
Background:
- Lack of consensus exists regarding the handling of missing data in next-generation sequencing (NGS) for phylogenetic and phylogeographic analyses.
- Some studies exclude loci with missing data, while others include them, even with substantial missingness.
- Restriction site Associated DNA (RAD) sequencing is a common NGS method for population genetics.
Purpose of the Study:
- To investigate the consequences of excluding missing data in NGS, specifically using RAD sequences.
- To highlight how decisions about missing data impact locus selection and the mutational spectrum.
- To evaluate the impact of library preparation and taxonomic diversity on missing data handling.
Main Methods:
- Simulations were used to model the effects of excluding missing data from RAD sequences.
- Analyses focused on the relationship between missing data thresholds and the characteristics of sampled loci.
- The influence of reduced representation libraries, coverage, and taxonomic divergence was assessed.
Main Results:
- Excluding missing data reduces the overall amount of phylogenetic information available.
- More stringent missing data thresholds disproportionately exclude loci with higher mutation rates, truncating the mutational spectrum.
- This bias is exacerbated by library preparation methods (reduced representation, coverage) and taxonomic divergence.
Conclusions:
- The common practice of conservatively removing loci with missing data may be misguided for phylogenetic and phylogeographic studies.
- Careful consideration of missing data handling is crucial to avoid biased inferences in NGS-based evolutionary analyses.
- Understanding these biases is essential for accurate species delimitation and evolutionary history reconstruction.
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