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

Abstract

BackgroundAccurate knowledge of the core components of substitution rates is of vital importance to understand genome evolution and dynamics. By performing a single-genome and direct analysis of 39,894 retrotransposon remnants, we reveal sequence context-dependent germline nucleotide substitution rates for the human genome.ResultsThe rates are characterised through rate constants in a time-domain, and are made available through a dedicated program (Trek) and a stand-alone database. Due to the nature of the method design and the imposed stringency criteria, we expect our rate constants to be good estimates for the rates of spontaneous mutations. Benefiting from such data, we study the short-range nucleotide (up to 7-mer) organisation and the germline basal substitution propensity (BSP) profile of the human genome; characterise novel, CpG-independent, substitution prone and resistant motifs; confirm a decreased tendency of moieties with low BSP to undergo somatic mutations in a number of cancer types; and, produce a Trek-based estimate of the overall mutation rate in human.ConclusionsThe extended set of rate constants we report may enrich our resources and help advance our understanding of genome dynamics and evolution, with possible implications for the role of spontaneous mutations in the emergence of pathological genotypes and neutral evolution of proteomes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3440-5) contains supplementary material, which is available to authorized users.

8-Oxo-7,8-dihydroguanine, friend and foe: Epigenetic-like regulator versus initiator of mutagenesis

“…Therefore, on the basis of this estimate, the epigenetic mark 5mC induces ~3-fold more mutations than OG. This is consistent with recent deep genome sequencing experiments that identified more C→T mutations than G→T [64]. The line that differentiates DNA modifications as mutagenic vs. epigenetic is blurred, and that should result in a reevaluation of modifications considered mutagenic.…”

Do exercise-associated genes explain phenotypic variance in the three components of fitness? a systematic review & meta-analysis

“…Such an omission makes it difficult to assess the exact role of the gene(s) as the minor and major alleles often affect the phenotype differently, as shown in this study with APOE alleles [ 17 , 18 ]. Different genes also interact to produce the final phenotypic response [ 65 ], and here Genome Wide Association Studies (GWAS) will play an increasingly important role in identifying these and the variants. Thus, Williams et al [ 65 ] identified a total of 97 genes that predicted trainability, and that the phenotype was dependent on several of these genotypes, which may contribute to approximately 50% of an individual’s trainability [ 65 ].…”

“…Different genes also interact to produce the final phenotypic response [ 65 ], and here Genome Wide Association Studies (GWAS) will play an increasingly important role in identifying these and the variants. Thus, Williams et al [ 65 ] identified a total of 97 genes that predicted trainability, and that the phenotype was dependent on several of these genotypes, which may contribute to approximately 50% of an individual’s trainability [ 65 ]. Further, a recent study by Al-Khelaifi et al [ 66 ] also uncovered novel genes and associations using GWAS [ 66 ].…”

“…Despite low study numbers (27 participants), MAFbx accounted for 34.36% of the total 10% variability. MAFbx has previously been found to be associated with muscle strength gains during exercise induced muscle hypertrophy [ 65 , 92 – 94 ]. In agreement, Mascher et al [ 93 ] found that this gene is involved in muscle breakdown and atrophy, and that resistance training reduced its expression, hence on this basis, might be associated with strength.…”

Structure-driven effects on genomic DNA damage propensity at G-quadruplex sites

“…Considering the immense biological relevance of the G4 sites (2,3,19) and their specific distribution in our genome (4,21,25,28,33,40), the differential influence of these loci on DNA damage can thus be an important non-specific driver of an emergent complexity in genome organisation and gene regulation. With intrinsic sequence effects on DNA damage and mutation acting at below 10 bp range (104,105), here we also establish a structuremediated meso-scale (~30 bp range on average) sequence effects on DNA damage susceptibilities, showcasing the different modes and magnitude of the effects depending on the damage type, relative strand localisation and G4 strength.…”