4.5: Some mutations may not have detectable phenotypes - Biology

4.5: Some mutations may not have detectable phenotypes - Biology

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Silent Changes

After mutagen treatment, the vast majority of base pair changes (especially substitutions) have no effect on the phenotype. Often, this is because the change occurs in the DNA sequence of a non-coding region of the DNA, such as in inter-genic regions (between genes) or within an intron region. Also, even if the change occurs in a base within a codon, it may not change the amino acid that it encodes (recall that the genetic code is degenerate; for example, GCT, GCC, GCA, and GCG all encode alanine) and is referred to as a silent mutation. Additionally, the base substitution may change an amino acid, but this doesn’t alter the function of the product, so no phenotypic change would occur.

Environment and Genetic Redundancy

There are also situations where a mutation can cause a complete loss-of-function of a gene, yet not produce a change in the phenotype, even when the mutant allele is homozygous. The lack of a phenotypic change can be due to environmental effects: the loss of that gene product may not be apparent in that environment, but might in another. Alternatively, the lack of a phenotype might be attributed to genetic redundancy, i.e. the encoding of similarly functioning genes at more than one locus in the genome. Thus the loss of one gene is compensated by another. This important limitation of mutational analysis should be remembered: genes with redundant functions cannot be easily identified by mutant screening.

Essential Genes and Lethal Alleles

Some phenotypes require individuals to reach a particular developmental stage before they can be scored. For example, flower color can only be scored in plants that are mature enough to make flowers, and eye color can only be scored in flies that have developed eyes. However, some alleles may not develop sufficiently to be included among the progeny that are scored for a particular phenotype. Mutations in essential genes create recessive lethal alleles that arrest the development of an individual at an embryonic stage. This type of mutation may therefore go unnoticed in a typical mutant screen because they are absent from the progeny being screened. Furthermore, the progeny of a monohybrid cross involving an embryonic lethal recessive allele may therefore all be of a single phenotypic class, giving a phenotypic ratio of 1:0 (which is the same as 3:0). In this case the mutation may not be detected.

Naming Genes

Many genes have been first identified in mutant screens, and so they tend to be named after their mutant phenotypes, not the normal function or phenotype. This can cause some confusion for students of genetics. For example, we have already encountered an X-linked gene named white in fruit flies. Null mutants of the white gene have white eyes, but the normal white+ allele has red eyes. This tells us that the wild type (normal) function of this gene is actually to help make red eyes. Its product is a protein that imports a pigment precursor into developing cells of the eye. Why don’t we call it the “red” gene, since that is what its product does? Because there are more than one-dozen genes that when mutant alter the eye colour; e.g. violet, cinnabar, brown, scarlet, etc. For all these genes their function is also needed to make the eye wild type red and not the mutant colour. If we used the name “red” for all these genes it would be confusing, so we use the distinctive mutant phenotype as the gene name. However, this can be problematic, as with the “lethal” mutations described above. This problem is usually handled by giving numbers or locations to the gene name, or making up names that describe how they die (e.g. even-skipped, hunchback, hairy, runt, etc.) .

Mutations: History and Induction | Genetics

In this article we will discuss about the history and induction of mutations.

History of Mutation:

The sudden heritable changes in genes, other than those due to Mendelian segregation and recombination constitute mutations. The idea of mutation first originated from observations of a Dutch botanist Hugo de Vries (in the 1880’s) on variations in plants of Oenothera lamarckiana (evening primrose) growing in Holland. This plant had been introduced from America and had grown wild in Europe.

De Vries collected seeds from Oenothera plants, raised plants from them, and analysed the progeny for transmission of traits showing variation. He found that heritable variations were distinct from environmental variations. He gave the name mutation (latin mutare meaning change) to heritable changes and in 1901 published a book entitled “The Mutation Theory”.

Although De Vries is credited with the discovery of the idea of mutations, it was realised almost half a century later that perhaps none of the plants studied by him actually showed a gene mutation. Instead, the heritable phenotypic variations observed by him were found to be due to rare crossovers between translocated chromosomes.

The early concepts of mutation therefore arose out of genetic studies of visible phenotypes. Later, by the middle of the twentieth century, the molecular basis of heredity began to be investigated. It became established that the transmission of hereditary traits takes place due to an accurate process of self-replication of the genetic material which is DNA.

Today gross structural changes in the genetic material at the level of chromosomes are classified under chromosomal aberrations. They are treated separately. Only alterations in a very localised region of the chromosome at the molecular level are called mutations. They may involve one or more genes or nucleotides in DNA.

Mutations therefore cause the substitution, deletion, addition or alteration of the sugar, base or phosphate of a nucleotide or of one more whole nucleotides. When mutations bring about a change in a single nucleotide they are called point mutations. When several nucleotides are altered, it results in gross mutations. The product of a mutation is called a mutant, and could be a genotype, cell, a polypeptide chain or an individual.

Mutations have been broadly categorized as somatic and germinal mutations. When a mutation occurs in a somatic cell, it does not change the whole organism, but produces a phenotypic change in the organ to which the mutant cell belongs. The resulting individual is a mosaic for mutant and normal tissues.

Navel oranges (so named because when, first discovered in South America, the orange had a shriveled, indented portion resembling the human navel), golden delicious apples, emperor seedless grapes, some horticultural varieties of flowering plants, and white sectors in the red eyes of Drosophila males are examples of somatic mutations. In plants somatic mutations are transmitted to the progeny by methods of vegetative propagation such as budding and grafting.

Germinal mutations take place in cells of the germ line. A classic example of germinal mutations and perhaps also the one first recorded is that of short-legged sheep. In 1791 a farmer named Seth Wright in New England, U.S.A. noticed a short-legged lamb which could not jump over the fence and run away like all the other sheep in his small flock. Considering this to be an advantage, he started breeding work on the short-legged lamb.

He had 15 ewes (females) and one ram (male) out of which he established a line of short-legged sheep. The name ancon was given to this breed (Greek meaning elbow), because the crooked looking forelegs showed resemblance to the human elbow.

The first short-legged lamb arose as the result of a recessive mutation in one of its recent ancestors. From the breeding work done in Wright’s farm the crosses indicated that this lamb was homozygous for the mutant gene and several of the ewes were heterozygous carriers. The same mutation is said to have occurred in a flock of sheep in Norway in 1925 and another breed of ancon sheep has been produced out of it.

Induction of Mutations:

In 1927 H. J Muller showed for the first time that mutations could be induced in Drosophila by use of external agents or mutagens. He was awarded Nobel Prize in 1946. When flies were irradiated with X-rays, he found that the offsprings showed new phenotypes which were similar to those produced by spontaneously occurring mutations.

He also found that increasing the dose of X-rays results in a linear increase in the frequency of mutations. By 1930s, it became established that physical agents such as X-rays, gamma rays, UV radiation, and some chemical agents are all effective as mutagens. At the same time L. J. Stadler demonstrated that X-rays could produce gene mutations in plants of barley. Mutagenesis by radiation and chemicals are discussed separately below.


Theoretical Background of Radiation:

An atom is composed of a positively charged nucleus and negatively charged electrons orbiting around the nucleus. The nucleus contains uncharged neutrons and positively charged protons. The electrons can move from one orbit to another.

An electron absorbs energy when it jumps to a high energy level, and releases energy when it moves to a lower energy level. The released energy is in the form of electromagnetic radiation. Visible and UV light, X-rays and gamma rays are all electromagnetic waves.

Radiation breaks chromosomes by a chemical reaction which requires energy. The mutagenic effect of radiation depends upon the amount and type of energy left in the tissue. Visible light is a less energetic radiation as it leaves energy in the form of heat. But the energetic radiations such as ultraviolet (UV) leave energy in the form of heat and activation which leads to chemical change.

Activation is the type of energy which makes an electron move from an inner to an outer orbit of the atom. X-rays and gamma rays are high energy radiations that not only heat and activate, but leave energy in the cell in the form of ionisation.

The Atomic Bomb Explosions at Hiroshima and Nagasaki:

On August 6, 1945 the atomic bomb exploded over Hiroshima killing over 78000 people and leaving many affected survivors who were studied for the effects of radiation on human beings. On August 9, a second atomic bomb was exploded over the city of Nagasaki. The words hibakusha (explosion affected person) and higaisha victim or injured person became understood to people in the world.

A number of individuals who had received extensive radiation had no children for several years. Many of the survivors have shown visible chromosome abnormalities such as breaks and translocations.

Persons over 30 years of age who had received more than 200 rads of radiation were found to be more sensitive to radiation than persons of the younger age group. About 2 per cent of survivors developed leukemia within the following decade. The children of survivors have not shown a detectable increase in genetic abnormalities.

E. Altenberg was first to show that ultraviolet radiation can induce mutations. UV rays have longer wavelengths than X-rays and gamma rays, hence they cannot penetrate tissues as deeply. Their mutagenic action is limited to bacteria, fungal spores or other free cells whose genetic material lies very near the irradiated surface. L.J. Stadler induced mutations in pollen grains of maize plants.

He found that UV rays with a wavelength of about 260 nm (Fig. 20.3) were more effective in mutagenesis. In fact the wavelength most readily absorbed by DNA also happens to be 260 nm, thus proving a direct correlation between UV induced mutations and DNA. The sun is a powerful source of UV.

As such the sun’s rays would be expected to cause widespread damage through mutations in all living organisms. But fortunately a layer of ozone in the upper atmosphere absorbs most radiation below 290 nm. The UV rays falling on DNA are absorbed by the pyrimidine bases especially thymine. Cross linking between adjacent pyrimidines takes place to form thymine dimers.

The two thymines join at their 4 and 5 positions to form a dimer. Dimer formation can take place between two thymine residues (TT), cytosine (CC) or uridine (UU) or two different pyrimidines (CT). When cytosine is exposed to UV a molecule of water is added across the double bond between the fourth and fifth carbon atoms (Fig. 20.4).

When heated or exposed to acidic conditions, the hydrated photoproduct can revert to the original form. If allowed to remain as such long enough, the hydrogen bonds between the pyrimidine and purine on the complementary strand break, leading to strand separation in that region. Both dimerisation and hydration of double stranded DNA affect DNA replication.

Chemicals as Mutagens:

Molecular Basis of Point Mutations:

Mutations which alter nucleotide sequences within a gene are of two types: base pair substitutions and frame shift mutations. In base pair substitution one base pair, for example AT may be replaced by another such as CG or GC. These are of two further types, namely transitions and transversions.

Transitions are base changes in which a purine is substituted by another purine as when A = T pair is replaced by a G = C pair or vice versa or when a pyrimidine is replaced by a pyrimidine such as when T = A is replaced by C = G, or vice versa. Transversions are alterations in bases in which a purine is substituted by a pyrimidine, that is, when an A = T pair is replaced either by T = A or C = G, and vice versa.

In frame shift mutations, (so called because they shift the normal reading frame of base triplets in mRNA) single base pairs are deleted from or added to DNA in interstitial position. The genetic code requires reading of consecutive base triplets from a fixed starting point. If a single nucleotide is inserted or deleted, it shifts the reading frame, and all the subsequent triplets are read off differently.

The entire portion of the polypeptide chain after insertion or deletion is translated wrongly, resulting in a “non-leaky” phenotype. Frameshift mutations therefore differ from base pair substitutions which produce “leaky” phenotypes by altering only one nucleotide in a single triplet, so that only one amino acid is wrongly placed.

Nonsense and Missense Mutations:

When a mutation in a triplet changes the codon so that it is recognised by another amino acid, it is called missense mutation. But if the mutation changes the codon for a specific amino acid into one which signals chain termination (nonsense codon), it is called a nonsense mutation.

Missense mutations occur more frequently than nonsense mutations, and usually result in single amino acid replacements in the polypeptide chain. Such a chain may still have biological activity. Nonsense mutations result in premature termination of polypeptide chains so that only fragments of chains are formed. The lengths of fragments depend upon the distance of the nonsense mutation from the starting codon.

Mutations by Chemicals:

This is the most powerful group of mutagens. Chemicals of this group bind in vitro to the N-7 position of guanine. In vivo the 0-6 position of guanine and the 0-4 of thymine are preferred. They transfer alkyl groups to the nitrogen atoms of the bases in DNA. Alkylation of guanine causes ionisation of the molecule and changes its base pairing specificities. Alkylated guanine pairs with thymine instead of cytosine.

Thus on replication there is a transition from a G = C to an A = T base pair. Alkylation of purines leads to hydrolysis of the sugar base linkage so that the purine base is lost from the backbone of the DNA molecule producing apurinic gaps.

When DNA replication takes place, almost any base may be inserted in the gap. Insertion of a wrong base in a gap produces transitions as well as transversions. There are some bi-functional alkylating agents which form cross links between guanines on the same or opposite strands of the double helix. This causes more frequent production of apurinic gaps.

Examples of alkylating agents are nitrosoguanidine, mustard gas and mustard compounds, ethyl methane sulphonate (EMS) and ethyl ethane sulphonate (EES), alkyl halides, sulphuric and phosphoric esters, ethylene imines and amides, and others.

They are said to be electrophilic (electron deficient) reactants because they combine with nucleophiles which have electron rich centers. These compounds are also described as radiomimetic because their effects resemble those of ionising radiation.

EMS is one of the most powerful mutagenic agents known. It can add an ethyl group (- CH2 CH3) to a guanine, and much less frequently to adenine. Due to ethylation guanine pairs with adenine leading to A – T⇋ G – C transitions. EMS also produces apurinic gaps into which any of the four bases may be inserted giving rise also to transversions.

Base Substitution by Tautomerism:

The purine-pyrimidine base pairs in double helical DNA are determined mainly by the positions of hydrogen atoms which cross link the bases. Normally A pairs with T and G with C. The bases however, can exist in alternative forms due to rearrangements (tautomeric shifts) in the hydrogen atoms. Tautomers are rare and unstable and can revert to the common form.

Watson and Crick suggested that if a base was present in its tautomeric form at the time of DNA replication, then a wrong base would be synthesised in the new strand. At the next replication cycle, the tautomer would revert back to its normal form, the two strands would separate, and this time the normal correct base would be synthesised on the new strand. This would result in substitution of one base pair for another, i. e., A ⇋ G and T⇋ C transitions would occur.

These are chemicals with structure similar to bases in normal DNA and become substituted for normal bases during DNA replication. The first base analogue studied was 5-bromouracil (5-BU) which has chemical structure similar to that of thymine (5-methyluracil) except that the methyl group of thymine is replaced by bromine.

If 5-BU is supplied to the medium containing growing bacterial cells 5-BU gets incorporated into DNA instead of thymine. The cells remain alive and grow, and since 5-BU has the same pairing properties as thymine, it does not lead to mutation at all. However, there are two tautomeric forms of 5-BU, the normal keto form and the rare enol form (Fig. 20.5).

When the rare enol form becomes incorporated into DNA, it pairs with guanine instead of adenine due to its hydrogen- bonding properties. The keto form however pairs with adenine. The enol form is short-lived and will eventually return to the keto form.

When DNA undergoes replication in the presence of thymine, the strand containing 5-BU (now in keto form) will synthesise an adenine in the complementary strand. In the next round of replication, the A strand will synthesise a T strand opposite it. In this way a GC pair would be replaced by an AT pair resulting in mutation of the transition type.

A similar case is that of 2-amino-purine (2-AP) which is a chemical analogue of adenine inducing AT ⇌ GC transitions. In the common form 2-AP pairs with thymine and there is no mutation. But when it exists in its tautomeric form (imino form) it forms two hydrogen bonds with cytosine. 2-AP therefore acts by first replacing adenine by shifting to its imino form, and then pairs with cytosine during replication. It also induces reversion in 5-BU induced mutants.

Nitrous acid (HNO2) acts on non-replicating DNA by removing amino groups of nitrogenous bases, converting adenine to hypoxanthine, guanine to xanthine and cytosine to uracil (Fig. 20.6). The conversions lead to AT → GC and GC → AT transitions as explained in the Figure. In a similar way hydroxylamine (NH2OH) changes hydroxy-methyl-cytosine into uracil leading to AT → GC transition. These mutations are able to reverse their own effects (back mutation) as well as those of other base analogues.

The acridine dyes act by intercalating themselves in DNA. Intercalating agents are planar polycyclic molecules which act by inserting themselves between the stacked base pairs of the double-stranded DNA molecule. This results in doubling of the distance between adjacent base pairs. Acridine mutations show a high rate of spontaneous reversion.

Usually reversion is due to a second suppressor mutation within the same gene that carries the primary mutation. Acridine induced mutations are ‘non-leaky’ as they result in total loss of function of the gene product. Acridines include important fluorochromes and antiseptics, phenanthridines (like ethidium bromide) used as trypanocides, and polycyclic hydrocarbons which are important carcinogens.

Certain chemicals like ethoxy-caffeine, urethane and formaldehyde produce organic peroxides and free radicals leading to mutations. They probably cause destruction of nucleic acid bases resulting in breaks in single strands.

Sister Chromatid Exchanges:

Sister chromatid exchanges (SCEs) represent the interchange of DNA replication products at apparently homologous chromosomal loci. In the recent years SCE analysis has gained importance as a sensitive method for study of DNA damage it seems that agents which induce SCEs are also active as mutagens and carcinogens (cancer causing agents). Some human genetic diseases deficient in DNA repair mechanisms show abnormalities in SCE formation and predisposition for cancer.

SCEs are induced in cells by incorporation of BrdU into DNA. The cells are treated with BrdU for one or two cycles. They are harvested at metaphase after the second cycle, stained and analysed. Besides BrdU, alkylating agents and proflavine also induce SCEs.

The exact mechanism resulting in SCE formation is not known. SCE analysis is useful for estimating the cytogenetic impact of some drugs given to patients in chemotherapy. A higher frequency of SCEs has been found in human beings exposed to environmental pollutants, or have cigarette smoking habits.

Phenotype and Genetic Variation

Genetic variation can influence the phenotypes seen in a population. Genetic variation describes the gene changes of organisms in a population. These changes may be the result of DNA mutations. Mutations are changes in the gene sequences on DNA. Any change in the gene sequence can change the phenotype expressed in inherited alleles. Gene flow also contributes to genetic variation. When new organisms migrate into a population, new genes are introduced. The introduction of new alleles into the gene pool makes new gene combinations and different phenotypes possible. Different gene combinations are produced during meiosis. In meiosis, homologous chromosomes randomly segregate into different cells. Gene transfer may occur between homologous chromosomes through the process of crossing over. This recombining of genes can produce new phenotypes in a population.

Audition Mutations

Missense mutations have been found in affected individuals in DFNA8/12 families, and a dominant negative mechanism has been proposed, although haploinsufficiency is also considered possible ( Verhoeven, K. et al., 1998 ). The reasons for the differences in age of onset and phenotypes among affected individuals in DFNA8/12 families is not clear. However, three missense mutations that change cysteine residues at positions 1057, 1619, and 1837 are associated with progressive loss. So far, seven different missense mutations have been reported and to some extent it appears that mutations in the vWF regions cause high-frequency hearing loss, while those in the ZP domain cause mid-frequency loss ( Naz, S. et al., 2003 ).

In the Lebanese DFNB21 family, the affected individuals were homozygous for a splice site mutation. More recently, Naz S. et al. (2003) reported exon 5 and exon 20 frameshift mutations in two consanguineous DFNB21 families from Iran and Pakistan. In both families the hearing loss was prelingual and in the moderate-to-severe range.


We would like to thank M.E. Hurles and R. Durbin for early discussions about the analyses performed. We would like to thank The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC) and the authors of all previous studies cited in Supplementary Data Set 1 for providing free access to their somatic mutational data. This work was supported by the Wellcome Trust (grant 098051). S.N.-Z. is a Wellcome-Beit Prize Fellow and is supported through a Wellcome Trust Intermediate Fellowship (grant WT100183MA). P.J.C. is personally funded through a Wellcome Trust Senior Clinical Research Fellowship (grant WT088340MA). J.E.S. is supported by an MRC grant to the Laboratory of Molecular Biology (MC_U105178808). L.B.A. is supported through a J. Robert Oppenheimer Fellowship at Los Alamos National Laboratory. P.H.J. is supported by the Wellcome Trust, an MRC Grant-in-Aid and Cancer Research UK (programme grant C609/A17257). This research used resources provided by the Los Alamos National Laboratory Institutional Computing Program, which is supported by the US Department of Energy National Nuclear Security Administration under contract DE-AC52-06NA25396. Research performed at Los Alamos National Laboratory was carried out under the auspices of the National Nuclear Security Administration of the US Department of Energy.


Base-Substitution Mutation Rate.

Although an earlier attempt to estimate the human mutation rate using disease-gene data focused only on nonsense mutations (8), more accurate estimates of both the mutational spectrum and per-site rates may be obtained by including missense mutations, as done in the present study. For example, one limitation of a focus on nonsense mutations is that no mutations to nucleotide C can be detected on the coding strand, as the three termination codons (TAA, TAG, and TGA) are devoid of C. In addition, because termination codons are A+T rich, and there is a substantial mutational bias in the direction of A+T (where “+” implies total composition across both strands) production (9), a focus on these three codons may yield an overestimate of the overall mutation rate. Finally, the inclusion of missense mutations substantially increases sample sizes.

For the genes involved in this study, the average rates of base-substitutional mutation are 11.63 (1.80) and 11.22 (3.23) × 10 −9 per site per generation for autosomal and X-linked loci (SDs in parentheses), respectively (Dataset S1). Modifying the latter estimate to scale to a 1:1 incidence of exposure across the sexes yields an autosomal equivalent estimate of 14.81 (4.26) × 10 −9 , which is not significantly different from the direct autosomal estimate. An average pooled estimate for genes that spend equal time in males and females is then 12.85 (1.95) × 10 −9 per site per generation. Many sources of error contribute to the locus-specific estimates in Dataset S1, but these will all be subsumed into the SE of the overall mean estimate.

Universal Mutation Pressure in Direction of A+T.

As in all well characterized species except Caenorhabditis elegans (10), the transition-to-transversion ratio for de novo mutations in humans is significantly greater than the value of 0.5 expected under a random mutation model (in which every nucleotide has an equal probability of mutating to each other state, one of which is always a transition Table 1) (9 ⇓ ⇓ ⇓ –13). This is primarily a consequence of a high incidence of G:C → A:T transitions (where the colon denotes a Watson–Crick bond between strands). The raw human mutation spectrum is also consistent with observations in all other well characterized eukaryotic species in exhibiting a preponderance of mutations in the direction of A+T versus G+C. This disparity is contrary to the expectation for a genome in mutation equilibrium, which would necessarily exhibit equal numbers of mutations in both directions.

Summary of the raw base-substitution mutational spectrum in humans, and comparison with the de novo spectrum for other model species

From the conditional mutation rates, i.e., the mutation rates weighted by the incidence of the starting base, it is possible to estimate the equilibrium A+T composition expected under mutation pressure alone (ref. 9, p. 130), and in all species with a well defined mutational spectrum this exceeds the actual A+T composition, even at silent sites (Table 2). As there is no evidence that all genomes are evolving toward new nucleotide-composition equilibria, the only explanation for this pattern is that directional mutational pressure toward A+T is countered by some form of selection in favor of C+G. Following the approach of Bulmer (14), under the assumption of drift-mutation-selection balance, it can be shown that the deviation of the observed base composition from the mutational expectation is entirely a function of 4Nes (2Nes for haploids). This composite parameter is equivalent to twice the ratio of the power of selection (s) to the power of drift 1/(2Ne), where Ne is the effective population size, and s is the average selective advantage of C+G nucleotides.

Conditional mutation rates, equilibrium A/T composition expected under mutation pressure alone, and magnitude of average scaled selective disadvantage of A/T

The resultant estimates of 4Nes fall in the narrow range of 0.35 to 1.61 across all species, implying that the average magnitude of selection operating on base composition at the nucleotide level is of the same order of magnitude as the power of drift in a wide variety of species. A similar level of constancy of 4Nes across microbes and multicellular eukaryotes has been noted previously with respect to nucleotide composition in the third positions of codons (9). Remarkably, using phylogenetic data, Kondrashov et al. (15) obtained an estimate of 4Nes of 1.00 for codon usage in the great ape lineage, which is virtually identical to the estimate provided here (0.99).

As there is little question that effective population sizes decline by several orders of magnitude from microbes to multicellular species (16), the approximate constancy of 4Nes for nucleotide usage across disparate taxa requires a substantial increase in s operating on nucleotide composition in multicellular lineages. Although translation-associated selection (e.g., codon bias) is likely to be a factor in the evolution of nucleotide usage in coding DNA, biased gene conversion in the direction of G+C composition appears to be an equally, if not more, powerful force that applies to all genomic regions in sexually reproducing species (9). However, because the power of gene conversion appears to be considerably greater in yeast than in animals (which have substantially lower rates of recombination per physical distance along chromosomes), this factor alone appears to be incapable of explaining the pattern noted previously. Still another factor favoring G/C composition is the enhanced stability of G:C relative to A:T Watson–Crick bonds.

Regardless of the causal mechanism(s), the existing data clearly indicate that the absolute intensity of selection favoring G+C composition is substantially magnified in species with reduced effective population sizes. This pattern is expected if the disadvantage of suboptimal nucleotides cumulatively increases as the genome-wide nucleotide composition deviates further from the selectively optimal state [a form of synergistic epistasis (17)]. As selection does not become effective until the selection coefficient of a mutation (s) approaches the power of drift (1/2Ne), under this hypothesis, one would expect the nucleotide composition to be driven from the selective optimum by mutation until s is approximately equal to 1/(4Ne), or equivalently 4Nes is ∼1.00. Once this critical value of s is reached, mutation pressure would be incapable of pushing nucleotide composition to a more extreme value, with the equilibrium being defined by the ratio of mutation pressures and a scaled selection parameter near 4Nes of approximately 1.00. Consistent with this view, the results in Table 2 imply average values of 4Nes across species equal to 1.02 (0.18), 1.04 (0.08), and 0.78 (0.18) for coding DNA, silent sites, and total genomic DNA respectively, none of which are significantly different from 1.0.

If this interpretation is correct, then genomes that are in mutation-selection-drift equilibrium will have an A+T composition defined by the bias in mutation pressure alone, the approximate expectation being: from equation 6.2 in Lynch (9), where m is the ratio of the summed mutation rates involving G+C → A+T changes to the summed rates involving G+C ← A+T changes. Although this invariant pattern is “universal” only in the context of the current collection of species with well defined mutational features, because the phylogenetic diversity of this group is very substantial, it is likely to have broad applicability.

The predominance of A:T → G:C and G:C → A:T changes among base-substitutional mutations in the human genome has previously been inferred by other methods, some potentially influenced by selection biases (18 ⇓ –20). In primates, C → T transitions arise at CpG dinucleotide sites approximately 15 times the mutation rate observed at other sites (8, 21), ostensibly because of the spontaneous oxidative deamination of methylated cytosines at CpG sites. Consistent with this view, CpG sites in Arabidopsis that are specifically methylated do have elevated mutation rates, although methylation alone does not completely explain the high rate of G:C → A:T transition in this species, even at CpG sites (11). It is common for the CpGs within human somatic cells to be 20% to 80% methylated (22), although the degree of methylation in germline cells is less clear, and in Drosophila and Caenorhabditis, which do not have detectable levels of methylation, other mechanisms must be responsible for the elevated rate of G:C → A:T mutation.

Insertions and Deletions.

In the human genome, small (1–50-bp) deletions are approximately three times as common as insertions of the same size, with both types of changes exhibiting very similar scaling with the size of the fragment involved in the mutational event (Fig. 1). In both cases, the mutation frequency declines with the 1.82 power of fragment size. Among segregating mutations in the human population, deletions are also 2.3 to 4.1 times more common than insertions (23, 24), consistent with the threefold bias at the mutational level assuming that both types of alterations are equally deleterious.

The size-frequency spectrum of insertion and deletion mutations in human genes, summed over autosomal-dominant and X-linked genes. The scaling of frequency (f) with length of the mutation (L) is f = 0.56L −1.82 (r 2 = 0.957) and f = 0.67L −1.82 (r 2 = 0.973) for insertions and deletions, respectively. These regressions exclude the plotted data points for mutations with size changes that are multiples of 3, which leave the reading frame intact and in some cases have minimal phenotypic effects (and therefore go undetected), and also only employ mutations in size classes up to L = 20, beyond which sample sizes are very small and sporadic. For the latter reason, the data beyond L = 10 are also pooled into windows of three base sizes and divided by 3 to retain the appropriate scale.

From the fitted functions in Fig. 1, which ignore 3n-sized mutations (some of which apparently go undetected because they leave the reading frame intact), the total numbers of expected 1- to 50-bp mutations in the data set (corrected for detectability) are 2,585 and 903 for deletions and insertions. Comparing these numbers with the expected number of base-substitutional mutations (after correcting for the number of undetected mutations of this sort see Methods), the extrapolated estimates of the deletion and insertion rates become 0.58 and 0.20 × 10 −9 per site per generation. Thus, taken together, insertion and deletion mutations are only approximately 6% as common as those involving single-base substitutions.

Cost of Introns.

The mutational cost of introns can be estimated in units of numbers of coding-site equivalents by considering the ratio of targets, RT (number of introns per gene divided by number of coding nucleotides per gene), and RM (number of observed mutations to defective alleles resulting from altered splicing divided by number resulting from coding-region alterations here defined by the total of all base-substitution mutations and all insertion/deletions smaller than 50 bp in length not known to affect splicing). The ratio of these ratios, RM/RT, provides an estimate of the average cost of an intron at a locus in units of numbers of coding nucleotides.

The average cost of an intron is approximately 30.8 (2.1) base pair equivalents (Fig. 2). In other words, in terms of the mutational target size to defective alleles, the addition of an intron to a human gene is on average equivalent to adding approximately 31 nucleotides to the coding region. This estimate is almost certainly downwardly biased because some coding-region mutations probably alter splicing (and go undetected in studies without cDNA sequencing) and some mutations undetected by target-locus sequencing may actually be deep within intron sequence (which, in almost all studies, has not been assayed).

The cost of introns in human genes in units of the cost of coding nucleotides. The solid diagonal line denotes the average ratio of the values on the vertical and horizontal axes, 30.8. The dashed lines, for reference, denote ratios of 10 (lower) and 100 (upper). Thus, the mutational cost of an intron in a typical human gene is equivalent to adding 30.8 coding nucleotides, and for the vast majority of loci this cost falls within the range of 10 to 100.

It should also be realized that the relative intron costs presented here are functions of the selective constraints on the coding DNA at a locus. All other things being equal, genes with very strong constraints on coding sequence will yield lower relative measures of intron costs at the locus, despite the fact that the absolute cost of introns (in units of numbers of nucleotides reserved for proper splice-site recognition) is likely to be relatively constant across loci.

A more direct estimate of the mutational cost of introns can be obtained as follows. Conservatively assuming that all mutations affecting splicing are detectable, then after correcting for the detectability of base substitutions, there appear to be approximately 0.036 splicing mutations per base-substitution in an average human gene, which for the loci analyzed here, implies a mutation rate to defective alleles associated with splice-site mutations of 69.6 × 10 −9 per intron per generation. Thus, taking into consideration that this estimate is likely to be downwardly biased, with an average of eight introns per protein region, a typical human gene experiences an elevation in the mutation rate to defective alleles of approximately 10 −6 per generation that an intron-free allele would otherwise avoid.

Glial Progenitors as Targets for Transformation in Glioma

Shirin Ilkhanizadeh , . Anders I. Persson , in Advances in Cancer Research , 2014

9 Concluding Remarks and Future Perspectives

The wide-spread distribution and life-long proliferative capacity of OPCs match the temporal and regional occurrence of gliomas, and therefore represent targets for transformation ( Fig. 1.6 ). Genetically distinct gliomas displaying PDGFRA amplifications, IDH1 R132H mutations, and H3F3A mutations express the OPC-related genes OLIG2, NKX2.2, PDGFRα and SOX10, implicating a common cell of origin ( Sturm et al., 2012 Verhaak et al., 2010 ). Even mesenchymal gliomas may arise from OPCs as novel data suggest that defined intrinsic factors and influence from the tumor microenvironment enable gliomas to toggle between proneural and mesenchymal phenotypes ( Bhat et al., 2013 Mao et al., 2013 ). An emerging focus on OPCs in gliomagenesis will provide critical information to researchers studying etiology, tumor microenvironment, and therapeutic intervention in glioma.

Figure 1.6 . OPCs, but not NSCs, are highly abundant in regions where IDH1 R132H mutant and H3F3A K27 mutant tumors arise in GBM patients, implicating their role in gliomagenesis.

Gene Koh and Xueqing Zou contributed equally to this work.


Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, UK

Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK

Gene Koh, Xueqing Zou & Serena Nik-Zainal

MRC Cancer Unit, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0XZ, UK

Gene Koh, Xueqing Zou & Serena Nik-Zainal

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SNZ, GK, and XZ contributed to manuscript writing. All authors read and approved the final manuscript.

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Twitter handles: Gene Koh (@GeneChChKoh), Xueqing Zou (@xueqing_zou), Serena Nik-Zainal (@SerenaNikZainal).

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  • Received February 14, 2018.
  • Accepted in final form May 21, 2018.
  • Copyright © 2018 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.

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