5 DNA Markers

Walter P. Suza; Faizo Kasule; Thomas Lübberstedt; and Madan K. Bhattacharyya

Introduction

Molecular or DNA markers reveal sites of variation in DNA. Variability in DNA facilitates the development of markers for mapping and detecting traits. Any DNA sequence can be genetically mapped, such as genes that lead to plant phenotypes. The prerequisite is that a polymorphism must be available for the sequence to be mapped; that is, there must be two or more different alleles. This can basically be a single nucleotide polymorphism (SNP), a single nucleotide variant at a specific position within the target sequence, or an insertion/deletion (INDEL) polymorphism. Target sequences can be amplified by various methods, including the Polymerase chain reaction (PCR), and subsequently visualized to generate “molecular phenotypes” comparable to visual phenotypes, which can be observed using appropriate equipment. Various molecular methods have been developed to visualize SNPs or INDEL polymorphisms at a low cost and high throughput, as discussed earlier. The main use of those SNPs and INDEL polymorphisms is as molecular markers. By genetic mapping as described above, linkage between genes affecting agronomic traits or morphological characters, and DNA-based SNP or INDEL markers can be established. It can be more effective in the context of plant breeding to select indirectly for markers (DNA or non-DNA) than directly for target traits. Reasons can include lower costs for marker analyses, the ability to run multiple such assays (for DNA markers) in parallel, the ability to select early and discard undesirable genotypes, or to perform selection before flowering, as well as codominant inheritance of markers, among others. This chapter discusses various types of markers used in plant breeding.

General Properties of DNA Markers

DNA markers are readily detectable DNA sequences whose inheritance can be monitored. The advantage of DNA-based markers is that they are independent of environmental factors. An ideal DNA marker should possess the following properties:

  1. Be highly polymorphic
  2. Display co-dominant inheritance (to discriminate homozygotes from heterozygotes)
  3. Occur at high frequency in the genome
  4. Display selective neutral behavior
  5. Provide easy access
  6. Be simple to evaluate with the available set of tools
  7. Display high reproducibility, and
  8. Facilitate easy exchange of data between laboratories

Historically, DNA markers can be grouped into three main categories: (1) hybridization-based markers, e.g., restriction fragment length polymorphism (RFLP) markers; (2) PCR-based markers, e.g., amplified fragment length polymorphism (AFLP), and simple sequence repeat (SSR); and (3) sequence or chip-based markers, e.g., some procedures for detecting single-nucleotide polymorphism (SNP) markers. Examples of molecular markers belonging to the above three categories are further discussed. Recall that you learned about the principle of PCR and the application of PCR in molecular marker analysis in Plant Breeding Methods and Molecular Plant Breeding.

DNA Versus Non-DNA Markers

Genetic markers are broadly classified into two groups. (1) DNA markers: those based

on the detection of DNA. (2) Non-DNA markers: those based on visually distinguishable traits, also referred to as morphological markers (e.g., flower color or seed shape); and those based on gene products, referred to as biochemical markers (e.g., RNA, protein, and other cellular metabolites).

The advantage of DNA markers is that they are not affected by environmental factors. However, the presence of a particular DNA sequence may not always lead to the expected expression of a trait of interest. This is because the expression of a specific allele depends on environmental conditions and interaction with other genes. Thus, even though an allele with a known effect on a particular trait is present, it might not result in the expected phenotype. Therefore, DNA markers serve as a measure of an individual’s genetic potential. The equivalent in human genetics is the concept of risk. Based on DNA information, it is possible to predict a patient’s risk of developing a particular condition (e.g., a 30% chance of getting pancreatic cancer at a certain age). However, whether this condition is expressed depends on other circumstances. In contrast, if RNA- or metabolite-based biomarkers for this cancer type are available, the onset of this condition can be predicted with high accuracy. Thus, non-DNA markers are indicative of an individual’s realized potential.

The advantage of morphological markers, also known as visible markers, is that they are generally easy to score. However, morphological markers are affected by environmental conditions, making their use less reliable across environments. Also, morphological markers are limited in number compared to the abundance of DNA markers. Biochemical markers are affected by the developmental stage of the plant and the cell type from which they are isolated. This must be carefully selected. This is a major difference compared to DNA-markers, which are stable and valid, independent of the tissue from which the respective DNA has been isolated. The World Health Organization defines a biomarker as any parameter that can be used to measure an interaction between a biological system and an environmental agent, which may be chemical, physical, or biological. Therefore, the diagnosis of a disease condition and the identification of possible treatments require the use of biomarkers. In conclusion, the term “biomarker” is broadly defined and may encompass both DNA- and non-DNA-based markers. However, the term biomarker is sometimes used in a narrower sense to refer to biochemical non-DNA markers.

To understand the relationship between DNA markers and non-DNA markers, review the pathways by which genetic information in deoxyribonucleic acid (DNA) is transferred from DNA to ribonucleic acid (RNA) molecules (called transcription), and then transferred from RNA to a protein (termed translation) by a code that specifies the amino acid sequence of the protein (see Chapter 1). Epigenetic mechanisms (Chapter 2), including DNA methylation and demethylation, as well as histone acetylation/deacetylation, may also impact gene expression (see Figure. 1).

Genetic information is transferred from DNA to RNA to make proteins, with epigenetic regulation, including DNA methylation and histone modification, influencing gene expression. DNA, RNA, and proteins are illustrated as potential molecular markers, and changes in the DNA sequence lead to variations in RNA, protein, and phenotype.
Figure 1 Scheme of genetic (and epigenetic) information pathways from DNA to RNA to protein. DNA, RNA, and proteins can be used as markers. If the sequence of the protein is known, it may be used to track the DNA (the gene) from which it was encoded. Variations in the DNA sequence result in variations in RNA and protein sequences. If a change in the amino acid sequence of an enzyme results in a change in its function, the observable phenotype (morphological or biochemical) can be used as a marker. Non-coding RNAs (e.g., miRNA) are also important. Many miRNA genes are expressed in specific tissues and developmental stages to regulate the expression of specific genes by affecting mRNA stability and translation.

Classical DNA Markers

RFLP

RFLPs involve cutting DNA into fragments, followed by separating the fragments in a gel and then transferring them to a nylon membrane for hybridization with a radioactive probe. The membrane is exposed to X-ray film. Patterns of variability in fragment size, or polymorphisms, are viewed on the autoradiograph, and RFLP patterns are scored among genotypes.

Strengths of RFLP

  • Co-dominance
  • No sequence information is required
  • Simplicity not requiring costly instrumentation
  • RFLP probe sequences can be used to develop additional markers, e.g., Indel

Weaknesses of RFLP

  • Analysis requires large amounts of high-quality DNA
  • Low genotypic throughput (few loci detected per assay)
  • Difficult to automate
  • Use of radioactive probes restricts the analysis to specific laboratories
  • Probes must be physically maintained, not allowing sharing between laboratories
  • Low selection for polymorphic parental lines makes it challenging to complete the RFLP map

SSR

SSRs are widely used markers based on the high rate of variation in microsatellite loci. SSRs represent a few to hundreds of highly variable tandem copies of DNA repeats. Such tandem repeats, typically consisting of one to four bases, are widespread in higher organisms. Many different microsatellite loci (>100,000) can be present in any plant species. SSRs are a result of slippage during DNA replication or unequal crossover during meiosis. SSRs were discussed in the context of Plant Breeding Methods.

Variation in SSRs is observed by developing locus-specific primers that anneal to sequences flanking the repeat region; PCR is subsequently used to amplify the target region. Alleles (fragments) are visualized as bands with different migration patterns on a gel after electrophoresis. However, more recently, capillary electrophoresis has been employed, which also enables multiplexing of up to approximately 16 SSRs per capillary. It is essential that you are familiar with some of the most common methods for developing PCR primers for SSR analysis.

Strength of SSR markers:

  • Hypervariable, multiple alleles (high PIC)
  • In silico development is straightforward

Weaknesses of SSR markers:

  • Capability for multiplexing limited (max. 10-15)
  • Affects costs/datapoint
  • Few intragenic SSRs

AFLP

The AFLP procedure combines RFLP and PCR. In AFLP, genomic DNA is digested with restriction enzymes, followed by a ligation step where adapters are added to both ends of the restriction fragments. PCR is carried out on the adapter-ligated mixture, using primers that target the adapter, but that vary in the base(s) at the 3’ end of the primer. Click here to learn about the steps to detect and analyze AFLP markers.

Strength of AFLP markers:

  • High marker index
  • Amenable to automation
  • Robust
  • No prior sequence information required
  • Special applications: Gene family profiling; Methylation assay
  • Established service company: KeyGene

Weakness of AFLP markers:

  • Random loci might differ between populations
  • Dominant marker system

Current DNA Markers

SNP

SNPs are single-nucleotide differences in the DNA of two individuals. However, the term SNP may be somewhat misleading because differences in alleles at polymorphic AFLP or RFLP loci can also result from single-base changes. A SNP can be linked to a gene of interest or part of a functional gene itself. The advantages of functional markers were discussed in Plant Breeding Methods. The DNA used as a SNP marker cannot be analyzed by gel electrophoresis in the same manner as other classical markers because the base pair number and length of the DNA for two alleles will be the same. Some of the principles exploited in SNP detection are shown in Figure 2 below.

The four common methods for detecting a single-nucleotide polymorphism. Panel A shows allele-specific base differences, Panel B shows restriction enzyme digestion when a SNP alters a restriction site, Panel C shows hybridization of allele-specific probes, and Panel D shows primer extension using allele-specific primers.
Figure 2 Examples of methods used in SNP genotyping, adapted from Syvänen (2001).

In Figure 2A, an A-to-G transition is described, including the various methods that can be used to detect the A- and G-alleles. In Figure 2B, restriction enzymes may be used for allele-specific cleavage of the target DNA when a SNP changes the restriction site for the enzyme. An example of this method was discussed in Plant Breeding Methods. In Figure 2C, two short probes are used to detect the polymorphism by hybridization. Only the probe that perfectly matches the target will be stable; a mismatch will be unstable. The probes are usually labeled with a fluorescent dye or radioisotope for detection by a laser scanner or autoradiography (e.g., Southern blot analysis). In Figure 2D, a method called primer extension is described. Primer extension uses two allele-specific primers that anneal to the target sequences adjacent to the SNP and have a nucleotide that is complementary to the SNP at the 3’ end. Only primers that match the target sequence ideally will be extended by the DNA polymerase. Defining the scale of the genotyping project is crucial for selecting an appropriate SNP identification approach. The table below provides cost estimates for SNP genotyping of 1000 individuals.

Overall, various genotyping approaches are available, ranging from low-throughput to high-throughput. Some platforms permit users to select custom SNPs, but the highest-throughput assays are available only in fixed content. Not all custom SNPs are compatible with every format, and multiple SNPs may be required to carry out most projects targeting specific SNPs. However, there are still trade-offs in terms of throughput, specifically between the number of samples and the number of SNPs to be analyzed. Ultimately, cost will dictate how a SNP project is designed. Regardless of the study, design, quality control, and tracking are crucial to the project’s success. Laboratory Information Management Systems (LIMS) are important in every study design. The following are examples of SNP genotyping systems that are commonly used by plant breeders.

Read: Syvänen, A. 2001. Accessing genetic variation: genotyping single-nucleotide polymorphisms. Nat Rev Genet. 2:930-942

Taqman Assay

TaqMan SNP assays are based on PCR using four oligonucleotide primers: (1) A set of forward and reverse primers that are designed and tested for each SNP, and (2) Two hydrolysis (Taqman) assay probes conjugated with fluorescent dyes and quenchers. Taqman probes are designed to anneal within a region of the PCR fragment resulting from the annealing of the forward and reverse primers. The quencher ensures that a dye does not fluoresce before Taqman probes have annealed to their target during PCR. The PCR reaction is catalyzed by a polymerase enzyme with 5′ to 3′ exonuclease activity. The 5′ to 3′ exonuclease activity is required to cleave the quencher from the dye, allowing fluorescence to be produced during PCR amplification.

Watch this video to learn more about how Tagman works.

Watch this video to learn more about how Tagman works.

MassArray System

The MassArray system utilizes highly multiplexed PCR reactions to simultaneously screen multiple mutation sites by primer extension, combined with Matrix-Assisted Laser Desorption/Ionization-Time of Flight mass spectrometry (MALDI-TOF-MS). The system provides a rapid and quantitative readout, allowing for the detection of mutations, gene copy number, methylation status, and the level of expression of allelic variants. Up to approximately 20 SNPs, multiplied by about 400 samples, can be analyzed at a time. The three key steps in SNP analysis using the Sequenom system are (1) Target amplification, (2) Primer extension, and (3) Signal detection and ratio analysis.

Read: Polyploid SNP Genotyping Using the MassARRAY System

Watch: MassARRAY® System by Agena Bioscience

Watch: MassARRAY® System by Agena Bioscience

GoldenGate Assay

The GoldenGate assay involves the addition of biotin to genomic DNA, which immobilizes the DNA on avidin-coated particles that bind biotin. The assay utilizes three oligonucleotide primers; two of these (P1 and P2) are specific for the two SNP alleles, and the third (P3) is a locus-specific primer tagged with a sequence for capture on solid support. In the reaction, allele- and locus-specific primers anneal to the genomic DNA, followed by extension using a DNA polymerase. After extension, the products are ligated to the tag sequence by a ligase. PCR primers containing fluorescence labels recognize the P1, P2, and P3 sequences. Extension products, containing fluorescence labels, are captured on the BeadArray, which includes complementary tag sequences for fluorescence detection.

Read: Single-nucleotide polymorphism genotyping in polyploid wheat with the Illumina GoldenGate assay.

Read: Toward genome-wide SNP genotyping

INDEL

Insertions and deletions (Indels) cause changes in the DNA sequence through the addition or removal of nucleotides (Figure 3). Indels can range in size from one or a few bases to multiple megabases. Small deletions—from a few base pairs to kilobases in length—most often arise from unequal crossover during meiosis.

Two types of small DNA mutations: an insertion caused by the addition of a cytosine base and a deletion caused by the loss of a thymine base, demonstrating how insertions and deletions alter DNA sequence length.
Figure 3 An insertion mutation caused by the insertion of a Cytosine base (C) into the genome, and a deletion mutation caused by a deletion of a Thymine base (T) in the genome. Indels can arise during DNA replication, when the nascent and template strands slip out of alignment, hence creating extra or missing nucleotides that are fixed as insertions or deletions in the new DNA strand.

Read: Indel arrays: an affordable alternative for genotyping.

General Application of DNA Markers

The rapid development of molecular genetics tools during the 1980s and 1990s enabled the identification of genetic variation at the molecular level, based on DNA sequence changes and their association with phenotypic differences. These DNA variations, or polymorphisms, can be exploited by plant breeders as markers for traits of interest. The growing availability of sequence data from large-scale sequencing projects, along with advances in next-generation sequencing technologies and bioinformatics, has dramatically reduced the cost of marker discovery and application. The principles and use of PCR and molecular markers were discussed earlier in Crop Genetics, while their application in plant breeding is covered in greater depth in Molecular Plant Breeding. In this chapter, we briefly highlight examples of how DNA markers are used in genetic fingerprinting, gene tagging, and backcrossing.

Genetic Fingerprinting

Genetic fingerprinting is a method that utilizes the unique characteristics of DNA to classify individuals into distinct or similar groups. Because the genomes of different individuals contain polymorphisms, a unique DNA profile can be established for a particular organism. This profile is specific to that individual, and as unique as a fingerprint.

An example of genetic fingerprinting used to confirm parentage is shown, where DNA banding patterns reveal that offspring share bands (thick black lines) with both parental genotypes, indicating the inheritance of genetic markers from each parent.
Figure 4 Genetic fingerprinting can be used to confirm parentage.

The concept of fingerprinting is increasingly being applied to determine the ancestry of plants and animals. Genetic fingerprinting can be used in the breeding of endangered species or commercially important crops, as it helps guarantee the authenticity of the plants. With the ability to obtain highly specific DNA profiles, genetic fingerprinting can help prove that new varieties qualify for intellectual or variety protection. For commercially important crops that are difficult to characterize phenotypically, genetic fingerprinting is a crucial tool for identifying genetic diversity within breeding populations. One of the earliest methods of genetic fingerprinting used hybridization-based RFLP markers. Examples of genetic fingerprinting data are provided in Figure 4 and Figure 5.

Gel image showing amplified fragment length polymorphism (AFLP) banding patterns for multiple genotypes, with shared and unique bands illustrating genetic similarity and diversity among individuals.
Figure 5 Example of a genetic fingerprint based on AFLP analysis.

Learning Activity

How can genetic similarity be estimated among the different genotypes in Figure 5?

Answer
Click to reveal
  • By calculating genetic similarity (i.e., genetic similarity = number of common bands divided by the number of all bands).

Genetic fingerprinting can be applied at all phases of cultivar development. The phases are described below.

Phase 1: Identifying Genetic variation:

  1. In parent selection
  2. In recurrent selection
  3. In assigning individuals to heterotic pools
  4. In choosing genetic resources

Phases 2 and 3: Developing variety parents or testing hybrids:

  1. To measure heterozygosity to predict hybrid performance
  2. In conducting backcrossing

Phase 4: Seed multiplication and variety protection:

  1. To ensure the purity of hybrids and blends
  2. For variety approval
  3. To identify “essentially derived varieties” (EDV)

Gene Tagging

Recall that in Crop Genetics, you learned that linkage analysis tests for the co-segregation of a marker and a trait of interest by calculating the frequency of recombination. Using sets of markers flanking a trait of interest, the likelihood of a recombination event occurring between two markers is related to the distance between them. Thus, the further the marker is from the gene controlling the trait, the greater the chance there is that recombination will occur between the gene and the marker. This implies that markers closest to the trait will segregate with the trait of interest. A marker linked to a gene controlling a gene of interest can serve as a “tag” for that gene/trait. An example of gene tagging is provided in Figure 6.

Image for gene tagging, where a codominant molecular marker is tightly linked to a gene controlling fruit size. Marker alleles segregate with dominant and recessive trait alleles, enabling the identification of genotypes through PCR band patterns.
Figure 6 An example of gene tagging with a molecular marker is completely linked to a trait of interest. A hypothetical gene, “A”, controls fruit size in tomatoes and is dominant over “a”. A co-dominant marker is available to identify individuals carrying either of the fruit size alleles. The marker “M” is linked to the dominant allele, and “m” to the recessive allele. The detection of markers M and m by PCR produces fragments that can be separated by gel electrophoresis.

Learning Activity

What might be the benefit(s) of tagging a gene with a molecular marker for a trait that can be phenotypically scored?

Answer
Click to reveal
  • To allow early selection, allowing individuals without the trait to be curled early
  • Phenotypic markers are affected by the environment
  • The marker evaluation can help to fix the desired allele (A)
  • For transgenic traits, plants homozygous for the recessive allele (wild type) can be identified for regulatory purposes

Backcrossing

Marker-assisted backcrossing involves three steps:

  • Step 1: Selection of donor allele at the markers linked to target genes to reduce loss of target allele due to recombination. In this step, markers are useful if a recessive allele controls the trait or when multiple resistance genes are to be obtained from the donor. Additionally, markers are useful for identifying environmentally sensitive genes and for expensive phenotypes, such as grain quality.
  • Step 2: Selection of recurrent parent allele at other linked markers. This step helps reduce linkage drag when introgressing wild or exotic germplasm.
  • Step 3: Selection of recurrent parent allele at unlinked markers throughout the genome (background selection). It is all a matter of probability to identify backcross progeny that are like the recurrent parent (Figure 7). Markers specific to the recurrent parent, referred to as background markers, can therefore be used to identify progeny that are genetically more similar to the recurrent parent.
Molecular markers are used to identify progeny with the highest proportion of the recurrent parent genome early in the breeding process. Marker-assisted backcrossing across generations, with donor genome segments(red circles) decreasing and recurrent parent(black) genome increasing.
Figure 7 Development of male sterility by marker-assisted backcrossing in maize. A male sterile donor is crossed with a fertile recurrent parent. Red and black charts depict the proportions of donor and recipient genomes, respectively. Red and black bars represent the chromosome segments of the donor and recurrent parent, respectively. Progeny containing the most significant proportion of the recurrent parent genome can be detected as early as the BC1 generation (red circle) using molecular markers and genetic fingerprinting (blue circle). Overall, the use of markers helps increase the pace of production of new male sterile lines.

Markers are useful for foreground selection of lines that have the donor allele in a heterozygous condition. An example of the use of markers for foreground selection is illustrated in Figure 8. Without a marker, it would be difficult to distinguish between progeny that are heterozygous for the male sterility trait (Msms) and those that are homozygous (MsMs), as both scenarios result in fertile plants. The use of a co-dominant marker linked to Ms/ms heterozygotes helps identify heterozygotes and eliminates the need to expend time and resources for selfing and scoring individuals based on pollen production.

The foreground selection in a backcross population is shown, where a molecular marker distinguishes heterozygous plants from homozygous fertile plants, eliminating the need for additional selfing and phenotypic screening.
Figure 8 The use of molecular markers for foreground selection. Backcross of (S)Msms to (N)MsMs produces fertile plants, but of different genotypes (Msms or MsMs). Selfing the MsMs BC1 progeny will produce all MsMs fertile plants. Selfing of BC1 Msms progeny will produce fertile and sterile plants in the ratio of 3:1. The use of a linked marker will help eliminate additional work to self and phenotypic screening of the plants.

Biochemical markers

RNA-Based Markers

Chapter 1 discussed the steps in gene expression, including transcription (the production of mRNA from DNA) and translation (the production of proteins from mRNA). Not all genes produce mRNA that can be translated into proteins. Specific genes are transcribed into non-coding RNAs (e.g., microRNAs–miRNAs or short-interfering RNAs–siRNAs) that serve a regulatory function during plant growth and development. A gene can be either “on” or “off” depending on the cell type, stage of development, and environmental signals, meaning that at any moment each cell makes coding and non-coding RNA from only a proportion of its genome.

Protein-Based Markers

Common protein markers are isozymes. Isozymes are enzymes with similar function derived from more than one locus. Isozymes are encoded by gene families resulting from duplication events. Isozymes are different from allozymes in that allozymes represent one enzyme derived from a single locus. Isozymes are analyzed using a procedure called electrophoresis, a technique that separates macromolecules on a gel through the application of an electric field and specific chemical staining (Figure 9). To be proper as markers, isozymes must be electrophoretically resolvable (i.e., bands can be clearly separated for visualization on a gel) and detectable by various in-gel assay methods.

Gel electrophoresis is used to separate isozymes, which are enzyme bands that migrate through a gel under an electric field and are visualized by specific staining to distinguish different enzyme variants.
Figure 9 Electrophoresis is a laboratory technique used to evaluate isozymes. (Illustration from NIH-NHGRI 2011).

The advantage of isozymes is that they are robust and highly reproducible. Additionally, isozymes exhibit codominant expression, meaning that both homozygotes can be distinguished from the heterozygote, and neither allele is recessive. However, isozymes are gene products, so they reveal only a small subset of the actual variation in DNA sequences between individuals and do not reveal variation in the non-coding regions of the genome. Other limitations of isozymes as markers include: (i) data complexity as a result of dimers or multimers of the enzymes; (ii) multi- allelic and multi-locus systems can interpret the banding patterns difficult; (iii) the system is limited to those enzymes that can be detected in situ, resulting in a narrow coverage of the genome; (iv) relatively few biochemical assays are available to detect isozymes; and (vi) the assay is based on a phenotype, and thus sensitive to the environment.

Currently, isozymes are used mainly for germplasm identification and population genetics studies. Other examples of the application of proteomic approaches are listed below.

  1. Two-dimensional polyacrylamide gel electrophoresis was used to detect polymorphic protein markers in several plant species.
  2. A proteomic approach was used to identify protein markers in lung cancer
  3. Isozymes were useful in developing the linkage map for tomato
  4. Evaluation of isozyme uniformity in a wild extinct insular plant [ Lysimachia minoricensis J.J. Rodr. (Primulaceae)

Metabolite-Based Biomarkers

In human health, transitions from a healthy state to a diseased state can often be characterized by changes in key cellular metabolites. A similar concept can be applied to plants, where specific metabolites can serve as biomarkers during growth and development. For example, Tarpley et al. (2005) identified a set of biomarker metabolites associated with different developmental stages in rice.

The main advantage of metabolite-based markers is that their concentrations are more directly linked to phenotypic traits than those of DNA markers. Consequently, establishing a set of metabolite biomarkers for a plant species can be valuable for predicting agronomic performance under various environmental conditions (Sulpice et al., 2009, 2010; Steinfath et al., 2010).

Two major techniques commonly used for metabolite profiling are: (1) mass spectrometry (MS) and (2) nuclear magnetic resonance (NMR) spectroscopy. Specific methods include gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and NMR. For instance, Skogerson et al. (2009) used these approaches to develop metabolite profiles for different wines as biomarkers of wine sensory properties. Such wine biomarkers can serve as cost-effective alternatives to traditional sensory panels and may also have applications in regulatory contexts, such as detecting product adulteration.

When evaluating biomarkers, there is typically a trade-off between the breadth of metabolic coverage and the quality of metabolite data. In other words, targeted analysis of a single metabolite or a specific metabolite class often yields higher-quality data than untargeted analyses that cover multiple chemical classes.

Chapter Summary

DNA markers are readily detectable DNA sequences whose inheritance can be tracked across generations. The growing availability of sequence data from large-scale genome sequencing projects, combined with advances in next-generation sequencing (NGS), marker systems, and bioinformatics tools, has significantly reduced the cost of marker discovery and application.

A marker linked to a gene controlling a trait of interest can serve as a “tag” for that gene, making it valuable for both foreground and background selection in backcrossing programs. Additionally, genetic fingerprinting using DNA markers is widely applied in breeding programs for endangered species and commercially important crops to verify genetic identity and ensure authenticity.

Beyond DNA markers, other types of molecular markers include RNA-based markers, protein-based markers, and metabolite-based markers.

References

Syvänen, A. 2001. Accessing genetic variation: genotyping single nucleotide polymorphisms. Nat. Rev. Genet. 2:930-942. https://doi.org/10.1038/35103535

Skogerson, K., Runnebaum, R., Wohlgemuth, G., Ropp, J.D., Heymann, H., and Fiehn, O. 2009. Comparison of gas chromatography-coupled time-of-flight mass spectrometry and H nuclear magnetic resonance spectroscopy metabolite identification in white wines from a sensory study investigating wine body. J. Agric. Food Chem. 57: 6899-6907.

Steinfath, M., Strehmel, N., Peters, R., Schauer, N., Groth, D., Hummel, J., Steup, M., Selbig, J., Kopka, J., Geigenberger, P., Dongen, J., T., V. 2010. Discovering plant metabolic biomarkers for phenotype prediction using an untargeted approach. Plant Biotechnol. J. 8:900-911.

Sulpice, R., Trenkamp, S., Steinfath, M., Usadel, B., Gibon, Y., Witucka-Wall, H., Pyl, E., Tschoep, H., Steinhauser, M.C., Guenther, M., Hoehne, M., Rohwer, J.M., Altmann, T., Fernie, A.R., and Stitt, M. 2010. Network analysis of enzyme activities and metabolite levels and their relationship to biomass in a large panel of Arabidopsis Accessions. The Plant Cell. 22: 2872–2893

Tarpley, L., Duran, A.L., Kebrom, T.H., and Sumner, L.W. 2005. Biomarker metabolites capturing the metabolite variance present in a rice plant developmental period. BMC Plant Biol. 5: 8

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Plant Molecular Genetics and Bioengineering Copyright © 2026 by Walter P. Suza; Faizo Kasule; Philip W. Becraft; Thomas Lübberstedt; and Madan K. Bhattacharyya is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, except where otherwise noted.

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