Question: What are the majority of mutations that are selected against?
About the article "Evolution", section "Biased mutation".

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In reality, viewing the fitness effects of mutations in these discrete categories is an oversimplification.
Attempts have been made to infer the distribution of fitness effects (DFE) using mutagenesis experiments and theoretical models applied to molecular sequence data.
Distribution of fitness effects, as used to determine the relative abundance of different types of mutations (i.e., strongly deleterious, nearly neutral or advantageous), is relevant to many evolutionary questions, such as the maintenance of genetic variation, the rate of genomic decay, the maintenance of outcrossing sexual reproduction as opposed to inbreeding and the evolution of sex and recombination.
In summary, DFE plays an important role in predicting evolutionary dynamics.
A variety of approaches have been used to study the distribution of fitness effects, including theoretical, experimental and analytical methods.
Mutagenesis experiment: The direct method to investigate DFE is to induce mutations and then measure the mutational fitness effects, which has already been done in viruses, bacteria, yeast, and "Drosophila".
For example, most studies of DFE in viruses used site-directed mutagenesis to create point mutations and measure relative fitness of each mutant.
In "Escherichia" "coli", one study used transposon mutagenesis to directly measure the fitness of a random insertion of a derivative of Tn10.
In yeast, a combined mutagenesis and deep sequencing approach has been developed to generate high-quality systematic mutant libraries and measure fitness in high throughput.
However, given that many mutations have effects too small to be detected and that mutagenesis experiments can detect only mutations of moderately large effect; DNA sequence data analysis can provide valuable information about these mutations.
Molecular sequence analysis: With rapid development of DNA sequencing technology, an enormous amount of DNA sequence data is available and even more is forthcoming in the future.
Various methods have been developed to infer DFE from DNA sequence data.
By examining DNA sequence differences within and between species, we are able to infer various characteristics of the DFE for neutral, deleterious and advantageous mutations.
To be specific, the DNA sequence analysis approach allows us to estimate the effects of mutations with very small effects, which are hardly detectable through mutagenesis experiments.
One of the earliest theoretical studies of the distribution of fitness effects was done by Motoo Kimura, an influential theoretical population geneticist.
His neutral theory of molecular evolution proposes that most novel mutations will be highly deleterious, with a small fraction being neutral.
Hiroshi Akashi more recently proposed a bimodal model for DFE, with modes centered around highly deleterious and neutral mutations.
Both theories agree that the vast majority of novel mutations are neutral or deleterious and that advantageous mutations are rare, which has been supported by experimental results.
One example is a study done on the distribution of fitness effects of random mutations in vesicular stomatitis virus.
Out of all mutations, 39.6% were lethal, 31.2% were non-lethal deleterious, and 27.1% were neutral.
Another example comes from a high throughput mutagenesis experiment with yeast.
In this experiment it was shown that the overall distribution of fitness effects is bimodal, with a cluster of neutral mutations, and a broad distribution of deleterious mutations.
Though relatively few mutations are advantageous, those that are play an important role in evolutionary changes.
Like neutral mutations, weakly selected advantageous mutations can be lost due to random genetic drift, but strongly selected advantageous mutations are more likely to be fixed.
Knowing the distribution of fitness effects of advantageous mutations may lead to increased ability to predict the evolutionary dynamics.
Theoretical work on the DFE for advantageous mutations has been done by John H. Gillespie and H. Allen Orr.
They proposed that the distribution for advantageous mutations should be exponential under a wide range of conditions, which, in general, has been supported by experimental studies, at least for strongly selected advantageous mutations.
In general, it is accepted that the majority of mutations are neutral or deleterious, with rare mutations being advantageous; however, the proportion of types of mutations varies between species.
This indicates two important points: first, the proportion of effectively neutral mutations is likely to vary between species, resulting from dependence on effective population size; second, the average effect of deleterious mutations varies dramatically between species.
In addition, the DFE also differs between coding regions and non-coding regions, with the DFE of non-coding DNA containing more weakly selected mutations. 
 in disease.
Genetic diseases.
Glycolytic mutations are generally rare due to importance of the metabolic pathway, this means that the majority of occurring mutations result in an inability for the cell to respire, and therefore cause the death of the cell at an early stage.
However, some mutations are seen with one notable example being Pyruvate kinase deficiency, leading to chronic hemolytic anemia. 
Neutral mutations are changes in DNA sequence that are neither beneficial nor detrimental to the ability of an organism to survive and reproduce.
In population genetics, mutations in which natural selection does not affect the spread of the mutation in a species are termed neutral mutations.
Neutral mutations that are inheritable and not linked to any genes under selection will either be lost or will replace all other alleles of the gene.
This loss or fixation of the gene proceeds based on random sampling known as genetic drift.
A neutral mutation that is in linkage disequilibrium with other alleles that are under selection may proceed to loss or fixation via genetic hitchhiking and/or background selection.
While many mutations in a genome may decrease an organism’s ability to survive and reproduce, also known as fitness, these mutations are selected against and not passed on to future generations.
The most commonly observed mutations detectable as variation in the genetic makeup of organisms and populations appear to have no visible effect on the fitness of individuals and are therefore neutral.
The identification and study of neutral mutations has led to the development of the neutral theory of molecular evolution.
The neutral theory of molecular evolution is an important and often controversial theory proposing that most molecular variation within and among species is essentially neutral and not acted on by selection.
Neutral mutations are also the basis for using molecular clocks to identify such evolutionary events as speciation and adaptive or evolutionary radiations. 
Neutral mutations are measured in population and evolutionary genetics often by looking at variation in populations.
These have been measured historically by gel electrophoresis to determine allozyme frequencies.
Statistical analyses of this data is used to compare variation to predicted values based on population size, mutation rates and effective population size.
Early observations that indicated higher than expected heterozygosity and overall variation within the protein isoforms studied, drove arguments as to the role of selection in maintaining this variation versus the existence of variation through the effects of neutral mutations arising and their random distribution due to genetic drift.
The accumulation of data based on observed polymorphism led to the formation of the neutral theory of evolution.
According to the neutral theory of evolution, the rate of fixation in a population of a neutral mutation will be directly related to the rate of formation of the neutral allele.
In Kimura’s original calculations, mutations with |2 N"s"|<1 or |"s"|≤1/(2N) are defined as neutral.
In this equation, N is the effective population size and is a quantitative measurement of the ideal population size that assumes such constants as equal sex ratios and no emigration, migration, mutation nor selection.
Conservatively, it is often assumed that effective population size is approximately one fifth of the total population size.
"s" is the selection coefficient and is a value between 0 and 1.
It is a measurement of the contribution of a genotype to the next generation where a value of 1 would be completely selected against and make no contribution and 0 is not selected against at all.
This definition of neutral mutation has been criticized due to the fact that very large effective population sizes can make mutations with little selection coefficients appear non neutral.
Additionally, mutations with high selection coefficients can appear neutral in very small populations.
The testable hypothesis of Kimura and others showed that polymorphism within species are approximately that which would be expected in a neutral evolutionary model.
For many molecular biology approaches, as opposed to mathematical genetics, neutral mutations are generally assumed to be those mutations which cause no appreciable effect on gene function.
This simplification eliminates the effect of minor allelic differences in fitness and avoids problems when selection has only a minor effect.
Early convincing evidence of this definition of neutral mutation was shown through the lower mutational rates in functionally important parts of genes such as cytochrome c versus less important parts and the functionally interchangeable nature of mammalian cytochrome c in in vitro studies.
Nonfunctional pseudogenes provide more evidence for the role of neutral mutations in evolution.
The rates of mutation in mammalian globin pseudogenes has been shown to be much higher than rates in functional genes.
According to neo-Darwinian evolution, such mutations should rarely exist as these sequences are functionless and positive selection would not be able to operate.
The McDonald-Kreitman test has been used to study selection over long periods of evolutionary time.
This is a statistical test that compares polymorphism in neutral and functional sites and estimates what fraction of substitutions have been acted on by positive selection.
The test often uses synonymous substitutions in protein coding genes as the neutral component, however, synonymous mutations have been shown to be under purifying selection in many instances. 
In genetics, complementation occurs when two strains of an organism with different homozygous recessive mutations that produce the same phenotype (for example, a change in wing structure in flies) produce offspring with the wild-type phenotype when mated or crossed.
Complementation will occur only if the mutations are in different genes.
In this case, each strain's genome supplies the wild-type allele to "complement" the mutated allele of the other strain's genome.
Since the mutations are recessive, the offspring will display the wild-type phenotype.
A complementation test (sometimes called a "cis-trans" test) can be used to test whether the mutations in two strains are in different genes.
Complementation will not occur if the mutations are in the same gene.
The convenience and essence of this test is that the mutations that produce a phenotype can be assigned to different genes without the exact knowledge of what the gene product is doing on a molecular level.
The complementation test was developed by American geneticist Edward B. Lewis.
If the combination of two genomes containing different recessive mutations yields a mutant phenotype, then there are three possibilities:  Mutations occur in the same gene.
One mutation affects the expression of the other.
One mutation may result in an inhibitory product.