Dataset Information

Robustness of birth-death and gain models for inferring evolutionary events.

ABSTRACT:

Background

Phylogenetic birth-death models are opening a new window on the processes of genome evolution in studies of the evolution of gene and protein families, protein-protein interaction networks, microRNAs, and copy number variation. Given a species tree and a set of genomic characters in present-day species, the birth-death approach estimates the most likely rates required to explain the observed data and returns the expected ancestral character states and the history of character state changes. Achieving a balance between model complexity and generalizability is a fundamental challenge in the application of birth-death models. While more parameters promise greater accuracy and more biologically realistic models, increasing model complexity can lead to overfitting and a heavy computational cost.

Results

Here we present a systematic, empirical investigation of these tradeoffs, using protein domain families in six metazoan genomes as a case study. We compared models of increasing complexity, implemented in the Count program, with respect to model fit, robustness, and stability. In addition, we used a bootstrapping procedure to assess estimator variability. The results show that the most complex model, which allows for both branch-specific and family-specific rate variation, achieves the best fit, without overfitting. Variance remains low with increasing complexity, except for family-specific loss rates. This variance is reduced when the number of discrete rate categories is increased.

Conclusions

The work presented here evaluates model choice for genomic birth-death models in a systematic way and presents the first use of bootstrapping to assess estimator variance in birth-death models. We find that a model incorporating both lineage and family rate variation yields more accurate estimators without sacrificing generality. Our results indicate that model choice can lead to fundamentally different evolutionary conclusions, emphasizing the importance of more biologically realistic and complex models.

SUBMITTER: Stolzer M

PROVIDER: S-EPMC4239551 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Robustness of birth-death and gain models for inferring evolutionary events.

Stolzer Maureen M Wasserman Larry L Durand Dannie D

BMC genomics 20141017

<h4>Background</h4>Phylogenetic birth-death models are opening a new window on the processes of genome evolution in studies of the evolution of gene and protein families, protein-protein interaction networks, microRNAs, and copy number variation. Given a species tree and a set of genomic characters in present-day species, the birth-death approach estimates the most likely rates required to explain the observed data and returns the expected ancestral character states and the history of character ...[more]

PMID: 25572914

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Project description:BACKGROUND:Through its ability to open pores in cell membranes, perforin-1 plays a key role in the immune system. Consistent with this role, the gene encoding perforin shows hallmarks of complex evolutionary events, including amplification and pseudogenization, in multiple species. A large proportion of these events occurred in phyla for which scarce genomic data were available. However, recent large-scale genomics projects have added a wealth of information on those phyla. Using this input, we annotated perforin-1 homologs in more than eighty species including mammals, reptiles, birds, amphibians and fishes. RESULTS:We have annotated more than 400 perforin genes in all groups studied. Most mammalian species only have one perforin locus, which may contain a related pseudogene. However, we found four independent small expansions in unrelated members of this class. We could reconstruct the full-length coding sequences of only a few avian perforin genes, although we found incomplete and truncated forms of these gene in other birds. In the rest of reptilia, perforin-like genes can be found in at least three different loci containing up to twelve copies. Notably, mammals, non-avian reptiles, amphibians, and possibly teleosts share at least one perforin-1 locus as assessed by flanking genes. Finally, fish genomes contain multiple perforin loci with varying copy numbers and diverse exon/intron patterns. We have also found evidence for shorter genes with high similarity to the C2 domain of perforin in several teleosts. A preliminary analysis suggests that these genes arose at least twice during evolution from perforin-1 homologs. CONCLUSIONS:The assisted annotation of new genomic assemblies shows complex patterns of birth-and-death events in the evolution of perforin. These events include duplication/pseudogenization in mammals, multiple amplifications and losses in reptiles and fishes and at least one case of partial duplication with a novel start codon in fishes.

Dataset Information

Robustness of birth-death and gain models for inferring evolutionary events.

Background

Results

Conclusions

Publications

Robustness of birth-death and gain models for inferring evolutionary events.

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