Mutagenesis tool

With these kits, you can mutagenize several sites in double stranded DNA using a single mutagenic oligonucleotide. You can start the primer search process by loading either the DNA sequence or the amino acid sequence directly from Entrez or from your local drive. When starting with the peptide sequence, you can use the " Expression System " option to translate it into a non-degenerate DNA sequence. MutaPrimer achieves this by using the codon frequency data for the selected expression system.

The translation tool can be used to display the proteins coded by the both wild and mutant DNA sequences. After loading the gene or protein of interest simply add the mutation information by specifying the mutation type using easy to use MutaPrimer screens. Launch the search, and voila! You will be presented with the best primers for assured experimental success.

MutaPrimer designs mutagenic primers that fully comply with the primer design guidelines published by Stratagene for their QuikChange site directed mutagenesis kits. According to the guidelines, the most important parameters are desired Tm and required lengths for the flanking regions.

Today, humankind is relying solely on 15—20 species for the entire world food production [ 7 , 8 ]. This genetic erosion eventually became a bottleneck and various techniques to induce mutations and artificially increase variation emerged in the middle of the last century [ 9 ].

Initially, X-ray radiation was used as a mutagen since it was readily available to researchers. Later, more sophisticated techniques such as gamma and neutron radiation were developed at newly established nuclear research centers. During and directly following the Second World War, radiation-based techniques were complemented by chemical mutagens that were less destructive, freely available, and easier to work with.

Pioneer work in this area was performed by Auerbach and others, who demonstrated an increased mutation frequency in Drosophila following exposure to mustard gas War Gas [ 13 , 14 ]. A few years later, this work was followed by the discovery of methane-sulphonates and other chemical mutagens, which are still in use today [ 15 ]. The goal in mutagenesis breeding is to cause maximal genomic variation with a minimum decrease in viability. Compared to chemical mutagens, both types of radiation cause damage on a larger scale and severely reduces viability [ 16 , 17 ].

Chemical mutagens have gained popularity since they are easy to use, do not require any specialised equipment, and can provide a very high mutation frequency.

Compared to radiological methods, chemical mutagens tend to cause single base-pair bp changes, or single-nucleotide polymorphisms SNPs as they are more commonly referred to, rather than deletions and translocations. Of the chemical mutagens, EMS ethyl methanesulfonate is today the most widely used. EMS selectively alkylates guanine bases causing the DNA-polymerase to favor placing a thymine residue over a cytosine residue opposite to the Oethyl guanine during DNA replication, which results in a random point mutation.

Mutations in coding regions can be silent, missense or nonsense. In noncoding regions, mutations can change promoter sequences or other regulatory regions, resulting in up- or downregulation of gene transcription. Aberrant splicing of mRNA, altered mRNA stability and changes in protein translation may also occur as a result of mutagenesis.

Thus, contrary to EMS, a shift can happen in either direction [ 18 ]. All three chemical mutagens are, as can be expected, strongly carcinogenic and should be handled with extreme care. In contrast to EMS and MNU, which are both liquid, Az is a solid dust in its ground state and the additional step of first dissolving the acutely toxic and volatile substance before application makes it less attractive to handle.

Through the years, mutagenesis has generated a vast amount of genetic variability and has played a significant role in plant breeding programs throughout the world. Notable examples are several wheat varieties e. As in conventional mutagenesis, TILLING seeds are exposed to a strong mutagenic compound, which introduces random mutations across the entire genome.

However, extra care is taken to achieve mutation saturation in the target genome. After mutagenesis, the seeds M 1 are planted and allowed to self-fertilise and produce a new generation of seeds M 2. Typically, one seed from each line is sown to produce the M 2 population and, DNA is isolated from every single M 2 plant. Provided the number of mutations per genome is high enough and the size of the population is large enough, it is likely that a mutated allele of all genes in the genome exists somewhere in the population.

There seems to be a strong correlation between the ploidy level and the induced mutation frequency. Diploid populations, on the other hand, often need to be in the range of tens of thousands [ 22 , 23 ]. Harvesting and cleaning of individual lines without cross-contamination, preparation, storage, and organization of several thousand bags of seed and their corresponding DNA samples can be laborious and require large amounts of space and resources.

Proper storage is of immense importance as many seeds rapidly lose viability if stored under improper conditions. In addition, tracking a TILLING population and associated data over several generations and maintaining numbers on seed availability is greatly facilitated by establishing a database and bar-coding system.

The power of TILLING was first demonstrated in model systems such as Arabidopsis and Drosophila [ 24 , 51 ], where it was shown that single mutations in specific genes could be identified. TILLING has later been successfully applied to a number of plant systems including barley, wheat, maize, rice, oat, pea, and soybean Table 1. Thus, this technology provides the breeders with a new and sophisticated tool for crop improvement.

Although screening generally centers around one or a few genes, availability of a reference genome theoretically allows for assembly and analysis of complete mutant genomes. This can be particularly useful in cases where a phenotype is readily visible but no candidate gene has been identified. However, this also puts a great demand both on the speed and price of sequencing technologies see Section 3.

It relies on the specific cleavage of mismatched bases formed as a result of repeated melting and reannealing of a PCR product amplified from a region of interest. If a mutation is present, a hybrid DNA molecule with a single mismatch will be generated.

It is then selectively cleaved with an endonuclease, typically Cel-1 or Endo-1, producing two shorter fragments that can be separated by polyacrylamide gel electrophoresis [ 25 ].

By incorporating fluorescent dye-tags of different colours in the forward and reverse PCR primers, the amplified fragments can then be identified by the Li-Cor instrument. A single Li-Cor can run a 96 lane gel and the sensitivity is high enough to allow up to fold pooling of samples, thus totaling samples per run in diploid organisms.

However, when screening large hexaploid genomes this number is reduced considerably due to the increased genomic complexity.

In addition, there are a number of inherent drawbacks with the Li-Cor method that need to be considered. Parameters like fluorescent dye-primer- and DNA concentrations as well as the ratio between the cleavage enzyme and PCR product concentrations all affect the results and need to be optimised. In addition, for an efficient detection of the fluorescent fragments and acceptable throughput, a specialised instrument is required.

On the other hand, the maximum length of amplicons using a Li-Cor system is as high as 1. Both Endo-1 and Cel-1 are relatively expensive, but a protocol is available describing how to isolate Cel-1 directly from celery stalks [ 52 ].

The resulting enzyme extract, CJE celery juice extract can replace purified enzyme in many applications, substantially reducing the price per reaction. For postrun gel analysis, GelBuddy is an application that helps automate band detection in electrophoretic gels while ParseSNP can predict the expected effect of the introduced SNP on protein function. A heterozygous mutation would appear as two new elution-peaks with the sum of their sizes equaling the original PCR product [ 24 ].

An 8-fold pool of samples is recommended in a diploid organism allowing 8 samples to be analyzed simultaneously, although diploid pools of up to fold are possible [ 23 ]. However, running several samples concurrently would require the use of several HPLCs, limiting its potential as a high-throughput screening platform. Regular electrophoresis using agarose or polyacrylamide PAGE gels has been proposed as a cheap alternative to Li-Cor systems for high-throughput screening.

However, due to the decreased sensitivity of the method compared to Li-Cor a larger amount of Cel-1 is required per sample, further stressing the need for home-made CJE. A mutated strand will add new peaks to the graph. The maximum fragment length is approximately 1. The detection limit is also high enough to resolve an 8-fold pool [ 32 ]. An alternative method to CE is conformation sensitive capillary electrophoresis CSCE where, contrary to standard CE techniques, enzymatic degradation is not necessary [ 37 ].

Using this method, an 8-fold pool of diploid DNA is possible, although the authors themselves recommend a 4-fold pooling [ 37 ]. All types of capillary electrophoresis suffer from a slight decrease in sensitivity owing to the use of intercalating dyes rather than fluorescent primers. However, analysis is very fast, around 5—10 minutes per run and the instrument can be upgraded to handle 96 lanes concurrently. The downside of CE is the high instrument cost requiring a substantial initial investment.

When the temperature is gradually increased, DNA-strands will melt apart causing a release of the dye and the total fluorescence will decrease in a predictable way. A mutation will cause a shift in the graph as the mismatched base changes the melting temperature. Heterozygotes are easily identified by comparison of normalised melting curves with those of homozygotes or wild-type samples [ 54 , 55 ].

HRM is especially useful when a specific region with known impact on protein structure is the target or when the gene of interest contains many short exons and thus a short read length is acceptable.

A drawback is that specialised software has to be used to interpret the different melt-curves. HRM has been successfully applied in identification of mutations in wheat [ 56 ], Medaka [ 57 ] , tomato [ 37 ], and Arabidopsis [ 43 ]. Matrix-assisted laser desorption ionization time-of-flight MALDI-TOF spectroscopy has, since its inception in , become a mainstay tool for analysis in the fields of polymer chemistry and proteomics. Once detected, the fragments can be reassembled in silico to provide a picture of the screened PCR product and to pinpoint mutations.

Recently, a new matrix of diaminobenzophenone DABP was introduced, for the analysis of nucleotides. Compared to traditional 3-HPA 3-hydroxy piccolinic acid , DABP has a fold greater salt tolerance while retaining a similar resolution and sensitivity [ 59 ]. The enzymatic degradation steps are simple and robust and do not require optimization of individual steps or titration of the enzymes used. The method is also very sensitive and is capable of identifying heterozygote mutations in a hexaploid organism.

Another potential benefit is that the method does not rely on heteroduplex formation, allowing for accurate detection of homozygous mutations without the need to pool samples.

In fact, a homozygous mutation would be more visible as it leads to the disappearance of a mass peak in the MALDI graph. Additionally, we developed a new software to accurately identify new SNPs Figure 1.

Next-generation sequencing NGS has significantly accelerated the prospects of identifying mutations at the whole-genome level. Decreasing sequencing costs due to improved technical accuracy, improved throughput, and increased capacity compared to only a few years ago has led to a great potential for NGS in TILLING.

While the average read length for is bases, Illumina only gives up to bases per read but in turn generates a much greater amount of sequence data. In addition, these technologies are under constant development both with regard to read length, data quality and the number of sequences generated.

Using 3-dimensional pooling it is possible to screen one or several genes of interest in a single FLX run. Illumina sequencing has also been adapted to high-throughput TILLING, and has been used to screen bread-wheat, durum-wheat, and rice populations [ 61 ]. As the amount of data generated from NGS is immense, some knowledge of bioinformatics and access to computational resources are invaluable during analysis.

In addition to already established techniques, a new technology based on single molecule sequencing, PacBio RS is now also available. This technique will be especially useful for nonsequenced genomes where no prior alignment scaffold exists due to its impressive read lengths, but has yet to be adapted to TILLING.

This work identified high allelic diversity of , tag SNPs that could be useful for QTL mapping and association studies [ 63 ]. These studies highlight the growing importance of high-throughput technologies in fields other than mutation screening. Contrary to traditional screening methods done by plant breeders, TILLING focuses on first identifying mutations within genes of interest and then linking those mutations to a specific phenotype.

However, this approach is only possible when a gene linked to the trait of interest is known and the gene sequence available. Using software and maps of conserved sequences within the gene it is then possible to predict which of the identified mutations that are most likely to cause changes in protein structure or aborted translation resulting in a nonfunctional product.

The potential phenotypes identified in this way can then be verified by anatomical, histological, physiological, or biochemical studies. Although theoretically straightforward, there are several problems that might arise during the screening process and subsequent analysis. Since the screening takes place at the DNA-level, enhancer and promotor mutations that are upstream of the gene of interest can be difficult, if not impossible to detect unless a full genomic sequence is available, which is not the case for most nonmodel systems.

Another complication stems from the fact that a single mutation, even if predicted to be deleterious does not necessarily affect overall cellular function. Homologs or paralogs of the gene of interest may still be expressed, leading to a low or nonexistent penetration of the mutation.

This is especially true for hexaploid plants where a homolog of the gene of interest may exist in all three genomes and when one allele is mutated, two others may compensate for the loss. In practice it is therefore often necessary to identify knockout mutations in all alleles by laborious screenings followed by time-consuming crosses to stack the different mutations in the same genome.

This can severely delay the development of the final trait. Despite these drawbacks, several groups have reported successes in linking genotypic change to novel phenotypes in a variety of crops.

Most noticeably in wheat, where traits related to the waxy phenotype [ 29 , 36 , 47 ] and grain hardness are being developed [ 36 ], in soybean where TILLING has proven useful in increasing the oleic acid content through the identification of mutations in the FAD1, 2, and 3 genes [ 65 ] and in Sorghum where lignin content has been decreased though mutation of COMT [ 35 ]. However, this does not exclude the fact that TILLING populations, as well as other mutagenised populations also can be used for phenotypic screens.

Macromolecular composition and quantity of bioactive compounds like lignin and other fibers, lipid, and starch content are all quality characters that cannot be scored in the field. Lignin is found in secondary plant cell walls and provides rigidity to the plant.

Lignin is considered a negative component in foragers as it blocks the digestion of cell-wall polysaccharides by microbial enzymes and is itself indigestible. Thus, crop varieties with lower lignin levels in the cell walls are preferred for feed since they are more energy efficient. A quick and economical assay for visually screening for altered lignin levels in seeds is the phloroglucinol-HCl assay Wiesner test [ 66 ].

We screened seeds from lines from an oat TILLING population [ 23 ] and identified 17 lines where the seeds had a reduced lignin stain intensity. For further confirmation, an acetyl-bromide method was then used for accurate quantification of lignin levels in the mutant seeds [ 22 , 67 , 68 ].

An example of the screen is illustrated in Figure 3 d. Increased levels of dietary components that directly interfere with cholesterol absorption or excretion and thereby contribute to lowered plasma cholesterol levels are also very important breeding goals. The advantage of a screen at the phenotypic level is that the target character is directly identified. The disadvantage, compared to a genotypic screening is that the specific mutation s mediating the phenotype remains undiscovered.

There are several other examples from the literature elegantly demonstrating the power of biochemical screens [ 71 — 73 ]. Fungal pathogens represent a major threat to global agriculture.

Global climate change with mild winters and higher humidity is expected to increase the problem even further. One particularly troublesome pathogen with high relevance in North America and Europe including Sweden is Fusarium [ 74 ]. Comprised of more than different species, Fusarium cause diseases in major agricultural crops like wheat, barley, maize, and oats.

In addition, Fusarium sp. A particular challenge is Fusarium head blight disease FHB , for which there are currently no satisfactory management strategies available and where fungicide treatments give mixed and unpredictable results, sometimes even worsening mycotoxin contamination [ 75 ]. Unfortunately, the variation in the breeding populations does not seem to be high enough to identify and develop lines resistant to the disease.

On the other hand, even for characters that vary considerably with environmental factors, like pathogen resistance, mutagenised populations could be used to identify resistant lines with a strong genetic component.

The trick is to design an in vitro assay with such a stringent selection that single rare lines with strong resistance against the disease can be identified. We tested this concept by designing a petri dish assay to identify Fusarium -tolerant oat from a mutated population with a high variety [ 22 ]. We placed 5 seeds from each line of the oat TILLING population on water agar and inoculated each seed with approximately spores of Fusarium culmorum. Since the spores have difficulties developing on the water agar they instead germinate on the seeds and the growing fungi, in turn hindering seed germination.

As can be seen in Figure 3 e , this infection is efficient and the selection is therefore extremely harsh. We screened lines and identified 63 lines that germinated despite the presence of the fungi. We graded the lines as moderately resistant, if at least one seed germinated and developed rudimentary roots and shoots, and resistant if several seeds germinated and developed further Figure 3 e.

At the two leaf stages, all plants in the field were sprayed with a mixture consisting of four different subspecies of F. The plants were watered regularly during the whole growth season to facilitate infection. The degree of infection was scored later in the season as pink pigment formation on the microaxes Figures 3 f and 3 g. Out of 43 lines, 26 were less infected than the most resistant commercial variety and all but three showed a higher resistance than the original Belinda cultivar.

Thus, this preliminary experiment seems very promising and indicates that phenotypic screening of mutagenised populations could be used to identify complex characteristics like pathogen resistance if the screening method is carefully designed. To be truly useful, identification of a strong genetic character in a mutagenised population by a phenotypic screening procedure should be followed by a characterization of the molecular event underlying the modified character. In plants with sequenced genomes, that is, where reference sequences are available, novel phenotypes can be characterised using a combination of whole-genome resequencing, linkage maps, and microarrays, providing a comprehensive picture of gene expression changes and newly introduced SNPs compared to wild-type specimens.

A classical example is the identification of a GA20 oxidase mutation as a cause for the semidwarf phenotype used in many commercial rice varieties. Using genetic maps, the trait was linked to a region of chromosome 1. Combined with the knowledge that the dwarf phenotype had reduced levels of gibberellic acid GA , a putative GA gene in that area was identified and sequenced using the rice reference genome as a base.

Microarray technology has also been successfully applied in rice and Arabidopsis to connect genome-wide variations to specific phenotypes [ 77 , 78 ]. However, next-generation technologies such as Illumina sequencing now outperform the more traditional microarray methods for SNP identification [ 79 ]. In one such approach, EMS-induced Arabidopsis Col-0 mutants with slow growth and light green leaves were screened to identify the causative mutations.

The recessive mutants were first crossed with the Landsberg erecta ecotype. DNA from F 2 individuals was then pooled and sequenced using Illumina sequencing to up to fold genome coverage. A software called SHOREmap was then developed to identify the mutations in the segregating population. The software detected a mutation causing serine to asparagine nonsynonymous codon change in the AT4G gene [ 80 ].

In yet another approach, Austin et al. They first screened the Arabidopsis EMS-treated Col-0 mutants for sensitivity to flupoxam that were previously known to affect cell wall assembly or integrity. The mutants were then crossed to Landsberg erecta ecotype.

Through an in-house developed statistical approach, they were able to correctly identify the causative mutations and hence the genes responsible for the phenotype [ 81 ]. Since a mutation does not necessarily need to be in an exon of the candidate gene, identifying a mutation may be difficult if a reference genome is unavailable.

Mutations such as promotor mutations, mutations changing genome structure, mutations upstream in the regulation pathway, and various micro-RNA mutations can all be responsible for the downstream effect. When a reference genome is not available, these factors can be extremely difficult and time-consuming to evaluate comprehensively.

In such cases, an initial approach would be to obtain as many mutants as possible and evaluate each one separately, re-sequencing all genes of interest and performing qPCR experiments to gauge any possible changes in expression among the candidate genes. Although difficult, it is not impossible to obtain a genotype-phenotype association this way. Using EST libraries instead of the fully sequenced genome, Feiz et al. A major caveat is that a link between genetic maps and genes are unknown in many cases, thus effectively robbing the researchers of a valuable selection tool for limiting the number of candidate genes.

Even though present elite cultivars are genetically fairly homogeneous, phenotypic differences between individual plants can always be seen in the field due to varying environmental factors. Cultivars grown at different sites with different fertilisation, pest and weed control regimes, weather conditions, and so on will exhibit differences not only in general plant architecture but also in quantity of specific macromolecules and metabolites.

However, the influence of the environmental factor varies with the mechanism by which each particular mutation mediate the phenotype. Thus, if the genetic factor is strong for a specific trait, the variation in the expression of the trait will be smaller.

Examples of genetically strong and visible characters are leaf shape, colour, and presence of pubescence on the leaves or stems since these do not change noticeably with the environment. Such characters are therefore used as markers to distinguish market varieties from each other. In the ideal case such a visible, stable trait can also be correlated to a more specific, but invisible quality character.

The experienced breeder could then score the quality character directly in the field even at varying environmental conditions. The key to a good selection strategy therefore involves the identification of environmentally stable phenotypes that correlate to a specific genotype.

However, often such correlations cannot be found for important quality characters like high fat, starch or protein content, fibre composition, reduced levels of toxic compounds, and enhanced postharvest processing properties. To identify these traits, more specific assays have to be performed.

The drawback is that such assays often are time consuming and expensive and cannot be performed on a large number of samples. On the other hand, if a mutagenised population with a very high variation is used, the probability of identifying a specific trait is increased and the number of assays needed to identify a certain quality character is decreased.

In addition, the probability of finding rare mutations knocking out transcription factors or other pleiotropic genes is increased. Such mutations will have a stronger penetration and the corresponding phenotype will be less affected by outer, environmental parameters. In this particular mutation, the genetic factor is strong enough to be easily detected by the naked eye during the entire growth season. Of course, nonvisible mutations that can only be detected biochemically can, in an analogous way, still be genetically strong.

Once identified in a mutagenised population and tested for genetic stability in the field, the character can be introgressed into breeding lines lacking that character.

Ideally, introgression should be done by the help of a marker since it reduces the number of necessary crosses and also ensures that as many random mutations as possible are eliminated from the mutagenised lines.

Such a marker could be visible, biochemical, or molecular. A molecular marker, that is, a mutation or other DNA rearrangement that cosegregates with a useful quality character is preferable and has several advantages compared to conventional phenotypic selection. Material for the assay can be collected from any tissue in the plant and at any developmental stage and the trait can often be scored very early in the plant growth cycle, even from seeds.

This saves time, labour, and field space. Molecular markers can also be used to select for complex characters as long as the linkage to the marker is strong enough. If a molecular marker correlates to disease resistance, resistance can be scored without having to challenge the plant with the pathogen. MMAS can be based on a mechanistic knowledge of how a particular mutation directly up-, downregulates, or completely knocks out a specific gene.

In such a case it will be closely linked to a specific phenotype. However, MMAS could also be indirect, and based on a statistically significant link to the phenotype. Semagn et al. Perhaps most importantly, MMAS can be automated and subjected to high-throughput screening.

By automating DNA isolation, pipetting, separation, and evaluation using robots, fluorescent detection techniques, automatic scripts, and so forth, the screening procedure can be speeded up enormously and performed on a large number of markers in parallel. During the last decade mutagenesis in breeding has again come of age. Plant mutagenesis, which increases the variation in crop plants that have been inbred for centuries, coupled with high-resolution genotypic or phenotypic screening methods allows breeders to select for traits that were very difficult to breed for only a few decades ago.

The introduction of new genetic variation in inbred elite cultivars offers a unique possibility to identify novel traits, while retaining the agricultural excellence of the lines. With the rapid accumulation of genetic data from a wide range of crop plants, the continuous decrease of the costs associated with whole-genome sequencing, and the development of high-resolution analytical techniques, we have reached a point were we stand to gain both time and money by adding this toolbox to more traditional breeding techniques.

Since markers are generated in the process, this approach also allows stacking of the useful characters, paving the way for the development of complex multigenic traits like abiotic stress resistance. Although still restricted to the capacity of the endogenous genome, mutagenesis and high-resolution screening will provide a very good complement to recombinant DNA technologies and genetically modified organisms GMOs in further development of crop plants that are better adapted to climate change and the increasing global population.

This is an open access article distributed under the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article of the Year Award: Outstanding research contributions of , as selected by our Chief Editors. Read the winning articles. Special Issues. Academic Editor: Manuel Talon.

Received 30 Aug Revised 02 Dec Accepted 15 Dec Published 22 Jan Abstract Plant mutagenesis is rapidly coming of age in the aftermath of recent developments in high-resolution molecular and biochemical techniques. Introduction Plant breeding began as early as 10, BC during the Neolithic revolution, when tribes of hunter-gatherers started their shift towards a sedentary and agrarian society [ 1 ].

Table 1. Figure 1. Figure 2. Overview of different methods to screen a mutagenised population and to develop a new stable character. Figure 3.

Red coloration denotes presence of lignin. Upper left Petri dish shows the Belinda control. The remaining dishes show examples of resistant lines. References P. View at: Google Scholar P. View at: Google Scholar L. Evans, Crop Evolution, Adaptation, and Yield , vol. Hillman and M. View at: Google Scholar C.

Murray, London, UK, 1st edition,