Literature DB >> 22319143

Inferring divergence of context-dependent substitution rates in Drosophila genomes with applications to comparative genomics.

Ran Chachick1, Amos Tanay.   

Abstract

Nucleotide substitution is a major evolutionary driving force that can incrementally and stochastically give rise to broad divergence patterns among species. The substitution process at each genomic position is frequently modeled independently of the other positions, although complex interactions between nearby bases are known to significantly affect mutation rates. Here, we study the evolution of 12 fly genomes using new algorithms for accurate inference of parameter-rich substitution models. By comparing models between lineages, we reveal the evolutionary histories of substitution rates at different flanking nucleotide contexts. We demonstrate these driving forces of molecular evolution to be constantly changing, suggesting that neutral drift of mutation rates is an important factor in the evolution of genomes and their sequence composition. This observation is used to develop a scalable approach for parameter-rich comparative genomics. By screening short DNA sequences, we demonstrate how homeoboxes and other transcription factor binding motifs are highly conserved based on our parameter-rich models but not according to standard conservation assays. With the increasing availability of genome sequences, rich substitution models become an attractive and practical approach for evolutionary analysis in general and comparative genomics in particular.

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Year:  2012        PMID: 22319143     DOI: 10.1093/molbev/mss056

Source DB:  PubMed          Journal:  Mol Biol Evol        ISSN: 0737-4038            Impact factor:   16.240


  3 in total

1.  Drosophila functional elements are embedded in structurally constrained sequences.

Authors:  Ephraim Kenigsberg; Amos Tanay
Journal:  PLoS Genet       Date:  2013-05-30       Impact factor: 5.917

2.  Net Evolutionary Loss of Residue Polarity in Drosophilid Protein Cores Indicates Ongoing Optimization of Amino Acid Composition.

Authors:  Lev Y Yampolsky; Yuri I Wolf; Michael A Bouzinier
Journal:  Genome Biol Evol       Date:  2017-10-01       Impact factor: 3.416

3.  EvoLSTM: context-dependent models of sequence evolution using a sequence-to-sequence LSTM.

Authors:  Dongjoon Lim; Mathieu Blanchette
Journal:  Bioinformatics       Date:  2020-07-01       Impact factor: 6.937

  3 in total

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