David M. Francis, The Ohio State University
Heather L. Merk, The Ohio State University
Deana Namuth-Covert, University of Nebraska-Lincoln
Molecular markers have great potential to assist breeders in developing improved varieties by complementing phenotypic selection. They work by either measuring directly or indirectly a specific DNA sequence difference between various genotypes. When these markers are found to be linked to a trait of interest, it can aid the breeder in more efficiently selecting the plants or lines to move forward in the program (forward selection). Markers can also be used to improve all other trait combinations in the germplasm, either by crossing out unwanted alleles or maintaining those of value (background selection). This module is structured to give an overview of the traditional view of molecular markers; as bands on a gel. Therefore, traditional markers indirectly measure DNA differences. With advances in DNA sequencing techniques, the cost of directly determining the sequence of a DNA fragment has dropped considerably. As a result, newer molecular marker tools are quickly becoming more common and are more effective in meeting plant breeding needs on a large scale. However, not all laboratories can currently afford to invest in the equipment required to take advantage of newer technologies and the newer technologies may not be more efficient on a small scale. You can also learn about this alternative view of molecular markers, where marker data is typically presented to breeders as fluorescence intensity values. This alternative view includes information about single nucleotide polymorphism (SNP) markers.
To understand the concepts behind any molecular marker system first requires an understanding of DNA and its structure, including the nucleotides and DNA base pairing.
- See an example of molecular markers being used to breed for tomatoes with improved resistance to bacterial spot.
Traditional View of Molecular Markers
This list of traditional molecular markers including their acronyms can give us some idea of the basis of the molecular marker. It also describes the differences (polymorphisms) in DNA sequences they target.
Isozyme: By measuring variations in enzymes, isozyme analysis exploits differences in the genes that code for or regulate enzyme synthesis or activity.
RFLP (Restriction Fragment Length Polymorphism): Indirectly measure DNA sequence differences based upon the varying lengths of DNA fragments resulting from cutting it with restriction enzymes. These “fragment length polymorphisms” are visualized by hybridizing the cut DNA with labeled probes from DNA libraries.
RAPD (Random Amplified Polymorphic DNA): Utilizing a large number of short DNA primers with varying sequences, this technique exploits differences in the primer binding sites as different DNA will be amplified by the polymerase chain reaction (PCR).
AFLP (Amplified Fragment Length Polymorphism): Utilizing restriction enzymes and a large number of short DNA primers with varying sequences, this technique exploits differences in the primer binding sites as different DNA will be amplified using PCR.
SSR (Simple Sequence Repeat) or microsatellite: Using PCR, this technique exploits differences in short repetitive sequences (e.g., CAA vs. CAACAACAA) by using specifically designed DNA primers that bind on each side of repetitive DNA sequences.
SCAR (Sequence Characterized Amplified Region): Exploit length differences between two PCR products (not necessarily repeats) by using specifically designed DNA primers that bind on each side of a difference in DNA sequence. These are often created by sequencing RAPD marker PCR products and then designing more specific DNA primers than are used for the original RAPD markers.
CAP (Cut/Cleaved Amplified Polymorphism): Exploit differences in DNA sequences between two PCR products based on the presence or absence of restriction enzyme cutting sites. These markers are often designed from RFLP markers.
Steps to Marker Detection
Each marker is detected differently, which allows us to look at the different types of variation listed above.
Isozyme: separate by starch gel and stain
RFLP: digest with restriction enzyme (RE), separate by agarose gel electrophoresis, transfer DNA to membrane, hybridize with labeled probe, visualize by autoradiography
Looking at the steps to marker detection can help us figure out how easy or difficult it may be to genotype using a particular molecular marker. For example, RFLP markers require a lot of steps and they also require steps that none of the other markers do, in particular creating a library of DNA or cDNA probes. This suggests that RFLPs take very specialized knowledge and laboratory skills to perform. People who have worked with RFLPs can tell you this is true! They likely prefer to work with markers that are PCR-based because once you have learned the PCR technique, you can work with many different types of molecular markers and PCR does not take long. Table 1 provides us with some more information to help us compare the different molecular markers. We know that PCR-based markers are advantageous, but the table provides us with some information we wouldn’t necessarily know based on the marker names or the detection steps alone. The additional resources listed at the end of this page can provide you with more in-depth information about these molecular markers.
|Molecular Marker||Type of Inheritance||PCR-Based?||Strengths||Limitations|
|Isozyme||Co-dominant||No – enzyme activity base||
For a further introduction to molecular markers, see Chapter 3 (p. 45–83), Introduction to Genomics, in:
- Liu, B. H. 1998. Statistical genomics: Linkage, mapping, and QTL analysis. CRC Press, Boca Raton, FL.
For an introduction to molecular markers, linkage mapping, QTL analysis, and marker-assisted selection written for professional plant breeders, see:
- Collard, B.C.Y., M.Z.Z. Jaufer, J. B. Brouwer, and E.C.K. Pang. 2005. An introduction to markers, quantitative trait locus (QTL) mapping and marker-assisted selection for crop improvement: The basic concepts. Euphytica 142: 169–196. (Available online at: http://dx.doi.org/10.1007/s10681-005-1681-5) (verified 24 Mar 2012).
Development of this page was supported in part by the National Institute of Food and Agriculture (NIFA) Solanaceae Coordinated Agricultural Project, agreement 2009-85606-05673, administered by Michigan State University. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the United States Department of Agriculture.