scholarly journals CpG Mutation Rates in the Human Genome Are Highly Dependent on Local GC Content

2004 ◽  
Vol 22 (3) ◽  
pp. 650-658 ◽  
Author(s):  
Karl J. Fryxell ◽  
Won-Jong Moon
Keyword(s):  
Human Genome ◽  
Gc Content ◽  
Mutation Rates

scholarly journals Recombination Drives the Evolution of GC-Content in the Human Genome

2004 ◽  
Vol 21 (6) ◽  
pp. 984-990 ◽  
Author(s):  
Julien Meunier ◽  
Laurent Duret
Keyword(s):  
Human Genome ◽  
Gc Content

scholarly journals Mutation rate variations in the human genome are encoded in DNA shape

2021 ◽  
Author(s):  
Zian Liu ◽  
Md Abul Hassan Samee
Keyword(s):  
Human Genome ◽  
Genetic Diseases ◽  
Mutation Rates ◽  
Local Context ◽  
Clear Understanding ◽  
Shape Features ◽  
Shape Information ◽  
Nucleotide Mutation ◽  
Nucleotide Interactions ◽  
Dna Shape

AbstractSingle nucleotide mutation rates have critical implications for human evolution and genetic diseases. Accurate modeling of these mutation rates has long remained an open problem since the rates vary substantially across the human genome. A recent model, however, explained much of the variation by considering higher order nucleotide interactions in the local (7-mer) sequence context around mutated nucleotides. Despite this model’s predictive value, we still lack a clear understanding of the biophysical mechanisms underlying the variations in genome-wide mutation rates. DNA shape features are geometric measurements of DNA structural properties, such as helical twist and tilt, and are known to capture information on interactions between neighboring nucleotides within a local context. Motivated by this characteristic of DNA shape features, we used them to model mutation rates in the human genome. These DNA shape feature based models improved both the accuracy (up to 14%) and the interpretability over the current nucleotide sequence-based models. The models also discovered the specific shape features that capture the most variability in mutation rates, and distinguished between the most and the least mutated sequence contexts, thus characterizing mutation promoting properties of the genomic DNA. To our knowledge, this is the first attempt that demonstrates the structural underpinnings of nucleotide mutations in the human genome and lays the groundwork for future studies to incorporate DNA shape information in modeling genetic variations.

scholarly journals Adaptive Evolution Hotspots at the GC-Extremes of the Human Genome: Evidence for Two Functionally Distinct Pathways of Positive Selection

2010 ◽  
Vol 2010 ◽  
pp. 1-7 ◽  
Author(s):  
Clara S. M. Tang ◽  
Richard J. Epstein
Keyword(s):  
Gene Expression ◽  
Human Genome ◽  
Genetic Instability ◽  
Evolutionary Rate ◽  
Gc Content ◽  
Active Chromatin ◽  
Potential Explanation ◽  
High Gene Expression ◽  
High Gene ◽  
Variant Genes

We recently reported that the human genome is ‘‘splitting’’ into two gene subgroups characterised by polarised GC content (Tang et al, 2007), and that such evolutionary change may be accelerated by programmed genetic instability (Zhao et al, 2008). Here we extend this work by mapping the presence of two separate high-evolutionary-rate (Ka/Ks) hotspots in the human genome—one characterized by low GC content, high intron length, and low gene expression, and the other by high GC content, high exon number, and high gene expression. This finding suggests that at least two different mechanisms mediate adaptive genetic evolution in higher organisms: (1) intron lengthening and reduced repair in hypermethylated lowly-transcribed genes, and (2) duplication and/or insertion events affecting highly-transcribed genes, creating low-essentiality satellite daughter genes in nearby regions of active chromatin. Since the latter mechanism is expected to be far more efficient than the former in generating variant genes that increase fitnesss, these results also provide a potential explanation for the controversial value of sequence analysis in defining positively selected genes.

scholarly journals Contrasting determinants of mutation rates in germline and soma

2017 ◽  
Author(s):  
Chen Chen ◽  
Hongjian Qi ◽  
Yufeng Shen ◽  
Joseph Pickrell ◽  
Molly Przeworski
Keyword(s):  
Somatic Mutations ◽  
Gc Content ◽  
Replication Timing ◽  
Germline Mutations ◽  
Mutation Rates ◽  
Coding Region ◽  
Expression Levels ◽  
Strand Asymmetry ◽  
Number Of Factors ◽  
Somatic Tissues

AbstractRecent studies of somatic and germline mutations have led to the identification of a number of factors that influence point mutation rates, including CpG methylation, expression levels, replication timing and GC content. Intriguingly, some of the effects appear to differ between soma and germline: in particular, whereas mutation rates have been reported to decrease with expression levels in tumors, no clear effect has been detected in the germline. Distinct approaches were taken to analyze the data, however, so it is hard to know whether these apparent differences are real. To enable a cleaner comparison, we considered a statistical model in which the mutation rate of a coding region is predicted by GC content, expression levels, replication timing, and two histone repressive marks. We applied this model to both a set of germline mutations identified in exomes and to exonic somatic mutations in four types of tumors. Germline and soma share most determinants of mutations; notably, we detected an effect of expression levels on germline mutations as well as on somatic ones. However, whereas in somatic tissues, increased expression levels are associated with greater strand asymmetry and decreased mutation rates, in ovaries and testes, increased expression leads to greater strand asymmetry but increased mutation rates. This contrast points to differences in damage or repair rates during transcription in soma and germline.

scholarly journals Mutation bias shapes gene evolution in Arabidopsis thaliana

2020 ◽  
Author(s):  
J. Grey Monroe ◽  
Thanvi Srikant ◽  
Pablo Carbonell-Bejerano ◽  
Moises Exposito-Alonso ◽  
Mao-Lun Weng ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
De Novo ◽  
Gene Evolution ◽  
Gc Content ◽  
Mutation Rates ◽  
Rate Variation ◽  
Recent Theory ◽  
De Novo Mutations ◽  
Coding Region ◽  
Mutational Hotspots

Classical evolutionary theory maintains that mutation rate variation between genes should be random with respect to fitness 1–4 and evolutionary optimization of genic mutation rates remains controversial 3,5. However, it has now become known that cytogenetic (DNA sequence + epigenomic) features influence local mutation probabilities 6, which is predicted by more recent theory to be a prerequisite for beneficial mutation rates between different classes of genes to readily evolve 7. To test this possibility, we used de novo mutations in Arabidopsis thaliana to create a high resolution predictive model of mutation rates as a function of cytogenetic features across the genome. As expected, mutation rates are significantly predicted by features such as GC content, histone modifications, and chromatin accessibility. Deeper analyses of predicted mutation rates reveal effects of introns and untranslated exon regions in distancing coding sequences from mutational hotspots at the start and end of transcribed regions in A. thaliana. Finally, predicted coding region mutation rates are significantly lower in genes where mutations are more likely to be deleterious, supported by numerous estimates of evolutionary and functional constraint. These findings contradict neutral expectations that mutation probabilities are independent of fitness consequences. Instead they are consistent with the evolution of lower mutation rates in functionally constrained loci due to cytogenetic features, with important implications for evolutionary biology8.

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