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Inference of natural selection from interspersed genomic elements based on polymorphism and divergence
Ilan Gronau1, Leonardo Arbiza, Jaaved Mohammed
1Department of Biological Statistics and Computational Biology, Cornell University, USA.
Molecular Biology and Evolution
|February 7, 2013
Summary
A new computational method, Inference of Natural Selection from Interspersed Genomically coHerent elemenTs (INSIGHT), accurately measures natural selection on short genomic elements. This method improves upon existing techniques by analyzing polymorphism and divergence data effectively.
Area of Science:
- Genomics
- Evolutionary Biology
- Computational Biology
Background:
- Complete genome sequences offer insights into natural selection.
- Analyzing selection on short, scattered noncoding elements is challenging.
- Existing methods struggle with the nuances of these elements.
Purpose of the Study:
- Introduce a novel computational method, INSIGHT, to quantify natural selection on short, noncoding genomic elements.
- Overcome limitations in accessing natural selection information from dispersed elements like transcription factor binding sites and small noncoding RNAs.
- Provide a robust tool for evolutionary and genomic studies.
Main Methods:
- Develop a generative probabilistic model to compare element polymorphism/divergence with flanking neutral sites.
- Pool information from numerous short elements, accounting for locus-specific mutation rates and coalescent times.
- Utilize a statistical phylogenetic approach with multiple outgroup genomes to assess divergence.
- Employ an approximate expectation-maximization algorithm for efficient genome-wide model fitting.
Main Results:
- INSIGHT accurately disentangles weak negative, strong negative, and positive selection based on distinct patterns.
- The method demonstrates robustness in complex demographic scenarios through simulations.
- INSIGHT significantly outperforms methods relying solely on summary statistics for polymorphism and divergence.
- Successful application to human noncoding RNAs and GATA2-binding sites validates its utility.
Conclusions:
- INSIGHT provides a powerful and accurate approach for inferring natural selection on short, noncoding genomic elements.
- The method enhances our ability to study evolutionary pressures on functionally important but hard-to-analyze DNA regions.
- INSIGHT opens new avenues for understanding the evolution of gene regulation and noncoding RNAs.
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