Prospects for building large timetrees using molecular data with incomplete gene coverage among species

Area of Science:

• Phylogenetics and Evolutionary Biology
• Bioinformatics and Computational Biology

Background:

• Construction of comprehensive timetrees relies on large sequence data sets.
• Missing data in species-gene matrices is common in large phylogenies.
• The impact of missing data on divergence time accuracy is not well understood.

Purpose of the Study:

• To systematically analyze the effect of missing gene data on divergence time estimation.
• To quantify the impact of data sparseness in large phylogenies using simulations and empirical data.

Main Methods:

• Computer simulations of phylogenies with varying degrees of missing data.
• Analysis of empirical data sets to assess divergence time accuracy.
• Identification of problematic nodes based on gene presence in descendant clades.

Main Results:

• Divergence time estimates remain robust even with a majority of missing gene data.
• Significant errors in time estimates occur at nodes lacking common genes in descendant clades.
• Problematic nodes can be identified pre-computationally from sequence alignments and tree topology.

Conclusions:

• Missing gene data has a surprisingly low impact on divergence time accuracy in large phylogenies.
• Identifying nodes with no common genes in descendant clades is crucial for detecting potential errors.
• Increasing the size of alignments by adding genes and species improves deep divergence time estimates.