Context dependent substitution biases vary within the human genome

Abstract

BackgroundModels of sequence evolution typically assume that different nucleotide positions evolve independently. This assumption is widely appreciated to be an over-simplification. The best known violations involve biases due to adjacent nucleotides. There have also been suggestions that biases exist at larger scales, however this possibility has not been systematically explored.ResultsTo address this we have developed a method which identifies over- and under-represented substitution patterns and assesses their overall impact on the evolution of genome composition. Our method is designed to account for biases at smaller pattern sizes, removing their effects. We used this method to investigate context bias in the human lineage after the divergence from chimpanzee. We examined bias effects in substitution patterns between 2 and 5 bp long and found significant effects at all sizes. This included some individual three and four base pair patterns with relatively large biases. We also found that bias effects vary across the genome, differing between transposons and non-transposons, between different classes of transposons, and also near and far from genes.ConclusionsWe found that nucleotides beyond the immediately adjacent one are responsible for substantial context effects, and that these biases vary across the genome.

Single genome retrieval of context-dependent variability in mutation rates for human germline

“…The aim of the machine learning procedure was to establish the optimal sequence length to minimise the error in the predicted rate constants (Figures S4 and S5 in Additional file 1). In agreement with prior evidence [9, 10, 44, 50], but now obtained for each individual i → j substitution type from Trek data, the optimal window was found to be 5-7-nt (both 5- and 7-nt resulting in comparable results for many substitution types) and was subsequently used as guidance for the direct mapping of the Trek rate constants from the L1 sequence onto any given human nuclear DNA sequence for the assignment.…”

“…To this end, the GBM models here had a sole purpose of identifying the optimal range of influence for accounting the neighbouring nucleotides. The optimal range was found to be captured, on average, by a 5-7-nt long window (Figures S4 and S5 in Additional file 1) which is in an excellent agreement with the prior < 10 nt estimate [9–11, 44, 50]. We thus used the maximum 7-nt length to stratify the Trek data for the further model-free mapping on any provided sequence, including the whole human genome.…”

“…There are distinct L1 subfamilies that were active at different time epochs, with detailed molecular clock analyses available [36–39] to reveal and, importantly, validate the age of each subfamily. They are well-represented and, unlike other classes of transposable elements, are uniformly scattered across mostly the intergenic regions of the human genome [34, 41, 42], and are less prone to recombination and context bias [43, 44]. The young L1 subfamilies have most of their remnants coming from the genomic regions with G+C content close to the genomic average value (Fig.…”

Context-Dependent Evolutionary Models for Non-Coding Sequences: An Overview of Several Decades of Research and an Analysis of Laurasiatheria and Primate Evolution

“…AT pressure, while the number of flanking pyrimidines on a single strand is correlated with a mutational bias, or skew, toward pyrimidines. Nevarez et al (2010) introduced an empirical method to examine context beyond immediately adjacent bases, based on the relative abundance method for studying word frequency bias. The authors used this method, which identifies over and underrepresented substitution patterns, to investigate context bias in the human lineage after the divergence from chimpanzee.…”

“…The authors used this method, which identifies over and underrepresented substitution patterns, to investigate context bias in the human lineage after the divergence from chimpanzee. Nevarez et al (2010) found that nucleotides beyond the immediately adjacent ones are responsible for substantial context effects and that these biases vary across the genome.…”