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The replication program of vertebrate genomes is driven by the chromosomal distribution and timing of activation of tens of thousands of replication origins. Genome-wide studies have shown the association of origins with promoters and CpG islands, and their enrichment in G-quadruplex motifs (G4). However, the genetic determinants driving their activity remain poorly understood. To gain insight on the constraints operating on origins, we conducted the first evolutionary comparison of origins across vertebrates. We generated a genome-wide map of chicken origins (the first of a bird genome), and performed a comparison with human and mouse maps. The analysis of intra-species polymorphism revealed a strong depletion of genetic diversity at the core of replication initiation loci. This depletion is not linked to the presence of G4 motifs, promoters or CpG islands. In contrast, we show that origins experienced a rapid turnover during vertebrate evolution, since pairwise comparisons of origin maps revealed that <24% of them are conserved among vertebrates. This study unravels the existence of a novel determinant of origins, the precise functional role of which remains to be determined. Despite the importance of replication initiation for the fitness of organisms, the distribution of origins along vertebrate chromosomes is highly flexible., (© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Genome evolution is shaped by a multitude of mutational processes, including point mutations, insertions, and deletions of DNA sequences, as well as segmental duplications. These mutational processes can leave distinctive qualitative marks in the statistical features of genomic DNA sequences. One such feature is the match length distribution (MLD) of exactly matching sequence segments within an individual genome or between the genomes of related species. These have been observed to exhibit characteristic power law decays in many species. Here, we show that simple dynamical models consisting solely of duplication and mutation processes can already explain the characteristic features of MLDs observed in genomic sequences. Surprisingly, we find that these features are largely insensitive to details of the underlying mutational processes and do not necessarily rely on the action of natural selection. Our results demonstrate how analyzing statistical features of DNA sequences can help us reveal and quantify the different mutational processes that underlie genome evolution., (© The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)