Mutation bias refers to a pattern in which some type of mutation occurs more often than expected under uniformity. The types are most often defined by the molecular nature of the mutational change (see examples below), but sometimes they are based on downstream effects, e.g., Ostrow, et al. refer to the tendency for mutations to increase body size in nematodes as a mutation bias.
Scientific context
The concept of mutation bias appears in several scientific contexts, most commonly in molecular studies of evolution, where mutation biases may be invoked to account for such phenomena as systematic differences in codon usage or genome composition between species. The short tandem repeat (STR) loci used in forensic identification may show biased patterns of gain and loss of repeats. In cancer research, some types of tumors have distinctive mutational signatures that reflect differences in the contributions of mutational pathways. Mutational signatures have proved useful in both detection and treatment.
Recent studies of the emergence of resistance to anti-microbials and anti-cancer drugs show that mutation biases are an important determinant of the prevalence for different types of resistant strains or tumors. Thus, a knowledge of mutation bias can be used to design more evolution-resistant therapies.
When mutation bias is invoked as a possible cause of some pattern in evolution, this is generally an application of the theory of arrival biases, and the alternative hypotheses may include selection, biased gene conversion, and demographic factors.
In the past, due to the technical difficulty of detecting rare mutations, most attempts to characterize the mutation spectrum were based on reporter gene systems, or based on patterns of presumptively neutral change in pseudogenes. More recently, there has been an effort to use the MA (mutation accumulation) method and high-throughput sequencing (e.g., ).
Examples of mutation biases
Transition-transversion bias
The canonical DNA nucleotides include 2 purines (A and G) and 2 pyrimidines (T and C). In the molecular evolution literature, the term transition is used for nucleotide changes within a chemical class, and transversion for changes from one chemical class to the other. Each nucleotide is subject to one transition (e.g., T to C) and 2 transversions (e.g., T to A or T to G).
Because a site (or a sequence) is subject to twice as many transversions as transitions, the total rate of transversions for a sequence may be higher even when the rate of transitions is higher on a per-path basis. In the molecular evolution literature, the per-path rate bias is typically denoted by κ (kappa), so that, if the rate of each transversion is u, the rate of each transition is κu. Then, the aggregate rate ratio (transitions to transversions) is R = (1 * κu) / (2 * u) = κ / 2. For instance, in yeast, κ ~ 1.2, therefore the aggregate bias is R = 1.2 / 2 = 0.6, whereas in E. coli, κ ~ 4 so that R ~ 2.
In a variety of organisms, transition mutations occur several-fold more frequently than expected under uniformity. The bias in animal viruses is sometimes much more extreme, e.g., 31 of 34 nucleotide mutations in a recent study in HIV were transitions. As noted above, the bias toward transitions is weak in yeast, and appear to be absent in the grasshopper Podisma pedestris.
Male mutation bias
Definition
Male mutation bias is also called "Male-Driven Evolution". The rate of male germline mutations is generally higher than in females. The phenomenon of Male mutation bias have been observed in many species.
Origin
In 1935, the British-Indian scientist J.B.S. Haldane found that in hemophilia, the blood clotting disorder originated on the X chromosomes is due to fathers' germline mutation. Then he proposed the hypothesis that the male germline contributes inordinately more mutations to succeeding generations than that in the female germline mutation.
Evidence
In 1987, Takashi Miyata at al. designed an approach to test Haldane’s hypothesis. If α is the ratio of the male mutation rate to the female mutation rate, Y and X are denoted as Y and X-linked sequence mutation rate, he include that the ratio of Y-linked sequence mutation rate to X-linked sequence mutation rate is: