See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/226925645 An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: The basic... Article in Euphytica · January 2005 DOI: 10.1007/s10681-005-1681-5 CITATIONS READS 741 5,893 4 authors, including: Bertrand C. Y. Collard Zulfi Jahufer 84 PUBLICATIONS 2,637 CITATIONS Massey University 33 PUBLICATIONS 1,019 CITATIONS SEE PROFILE SEE PROFILE Edwin Chi Kyong Pang RMIT University 73 PUBLICATIONS 2,326 CITATIONS SEE PROFILE Some of the authors of this publication are also working on these related projects: Developing low-cost, simple, gel-based DNA marker methods focusing on gene regions View project Novel Markers for Drought Resistance in White Clover View project All content following this page was uploaded by Edwin Chi Kyong Pang on 08 January 2015. The user has requested enhancement of the downloaded file. Euphytica (2005) 142: 169–196 DOI: 10.1007/s10681-005-1681-5 C Springer 2005 An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: The basic concepts B.C.Y. Collard1,4,∗ , M.Z.Z. Jahufer2 , J.B. Brouwer3 & E.C.K. Pang1 1 Department of Biotechnology and Environmental Biology, RMIT University, P.O. Box 71, Bundoora, Victoria 3083, Australia; 2 AgResearch Ltd., Grasslands Research Centre, Tennent Drive, Private Bag 11008, Palmerston North, New Zealand; 3 P.O. Box 910, Horsham, Victoria, Australia 3402; 4 Present address: Plant Breeding, Genetics and Biotechnology Division, International Rice Research Institute (IRRI), DAPO Box 7777, Metro Manila, Philippines; (∗ author for correspondence: e-mail:
[email protected]) Received 11 July 2004; accepted 2 February 2005 Key words: bulked-segregant analysis, DNA markers, linkage map, marker-assisted selection, quantitative trait loci (QTLs), QTL analysis, QTL mapping Summary Recognizing the enormous potential of DNA markers in plant breeding, many agricultural research centers and plant breeding institutes have adopted the capacity for marker development and marker-assisted selection (MAS). However, due to rapid developments in marker technology, statistical methodology for identifying quantitative trait loci (QTLs) and the jargon used by molecular biologists, the utility of DNA markers in plant breeding may not be clearly understood by non-molecular biologists. This review provides an introduction to DNA markers and the concept of polymorphism, linkage analysis and map construction, the principles of QTL analysis and how markers may be applied in breeding programs using MAS. This review has been specifically written for readers who have only a basic knowledge of molecular biology and/or plant genetics. Its format is therefore ideal for conventional plant breeders, physiologists, pathologists, other plant scientists and students. Abbreviations: AFLP: amplified fragment length polymorphism; BC: backcross; BSA: bulked-segregant analysis; CIM: composite interval mapping; cM: centiMorgan; DH: doubled haploid; EST: expressed sequence tag; SIM: sim- ple interval mapping; LOD: logarithm of odds; LRS: likelihood ratio statistic; MAS: marker-assisted selection; NIL: near isogenic lines; PCR: polymerase chain reaction; QTL: quantitative trait loci; RAPD: random amplified poly- morphic DNA; RI: recombinant inbred; RFLP: restriction fragment length polymorphism; SSR: simple sequence repeats (microsatellites); SCAR: sequence characterized amplified region; SNP: single nucleotide polymorphism; STS: sequence tagged site Introduction not possible. A major breakthrough in the characteri- zation of quantitative traits that created opportunities Many agriculturally important traits such as yield, qual- to select for QTLs was initiated by the development of ity and some forms of disease resistance are controlled DNA (or molecular) markers in the 1980s. by many genes and are known as quantitative traits (also One of the main uses of DNA markers in agricul- ‘polygenic,’ ‘multifactorial’ or ‘complex’ traits). The tural research has been in the construction of linkage regions within genomes that contain genes associated maps for diverse crop species. Linkage maps have with a particular quantitative trait are known as quan- been utilised for identifying chromosomal regions titative trait loci (QTLs). The identification of QTLs that contain genes controlling simple traits (controlled based only on conventional phenotypic evaluation is by a single gene) and quantitative traits using QTL and (3) DNA Kelly & Miklas. many plant ers which themselves are phenotypic traits or charac- breeding institutions have adopted the capacity for ters. molecular biology research but need an understanding sist in phenotypic selection. maize (Stuber et al. 1999. electrophoresis and specific staining. MAS involves using the as students who are not necessarily engaged in applied presence/absence of a marker as a substitute for or to as. 1997. will enable plant ized phenotypic characters such as flower colour.. 1995) and pasture species (Jahufer the phenotype of the trait of interest because they are et al. 1994). 1995). the authors of these reviews assumed of constructing linkage maps and conducting QTL that the reader had an advanced level of knowledge in analysis–to identify genomic regions associated with molecular biology and plant genetics. Young. 1994. Our review has been specifi- Mohan et al. 1995). barley (Thomas. McCouch & Doerge. ers are that they may be limited in number and are sis and the application of markers in marker-assisted influenced by environmental factors or the develop- selection (for example: Haley & Andersson. 1999. Generally... Paterson.170 analysis (reviewed by Mohan et al. Williams. Some studies suggest that DNA markers located only near or ‘linked’ to genes controlling the will play a vital role in enhancing global food produc. tuber Genetic markers represent genetic differences between crops (Barone.’ ‘gene’ ble exceptions of the reviews by Paterson (1996a. (singular ‘locus’). This review consists of five sections: genetic compared to the more conventional plant breeding markers. and Jones et al. 2003. 1998). Staub et al. as well (Ribaut & Hoisington. Isozyme mark- disciplines to work together towards a common goal ers are differences in enzymes that are detected by – increasing the efficiency of global food production. construction of linkage maps. 2003. Winter & Kahl. represent the target genes themselves but act as ‘signs’ Muehlbauer et al. which include allelic marker development and/or MAS (Eagles et al. QTL analy. The use of DNA markers in plant (and towards marker-assisted selection and marker-assisted animal) breeding has opened a new realm in agriculture selection. The process 1994). 1996a. Morphological markers are usually visually character- nology used by molecular biologists.b) or ‘genome’ mapping) (McCouch & Doerge. Ortiz. Genetic markers that are located in close et al. 1993. Gebhardt individual organisms or species. oilseeds (Snowdon & Friedt.. 2003). 1997. The major dis- A number of excellent reviews have been written advantages of morphological and biochemical mark- about the construction of linkage maps. Such markers themselves do not affect Mehlenbacher. Tuberosa et al. An understanding (or molecular) markers.. 2004. 2001). effective.b. It will be a (called gene ‘tagging’) may be used as molecular tools useful reference for conventional plant breeders. 1995). 1999.. 1996.. Weeden or ‘flags’. 1993). to as gene ‘tags’. methodology. wheat (Eagles et al. 2003). Van Sanford What are genetic markers? et al. 2002). However. in a way which may make of the exciting opportunities offered by this new tech- it more efficient.. 2003. 2001). physi- for marker-assisted selection (MAS) in plant breeding ologists. 1991a. Paterson et al. 1998). 2001. Al.. tightly linked) may be referred horticultural crop species (Baird et al. All genetic markers occupy specific genomic po- tion by improving the efficiency of conventional plant sitions within chromosomes (like genes) called ‘loci’ breeding programs (Kasha. which reveal sites of varia- of the basic concepts and methodology of DNA marker tion in DNA (Jones et al. they do not & Valkonen. reliable and cost-effective nology.. morphological and 1996a.e...b). 1997. 1997. Svetleva et al. (2) biochemical markers.. 2001. 2004). despite these limitations. with the possi- traits–is known as QTL mapping (also ‘genetic. proximity to genes (i. including some of the termi. 1995. Jones et al.. However. 1997. DNA markers cally written for readers with only a basic knowledge that are tightly linked to agronomically important genes of molecular biology and/or plant genetics. Tanksley. DNA markers are widely accepted as potentially valuable tools for crop improvement in rice (Mackill Section I: Genetic markers et al. 1998. 1997). seed breeders and researchers working in other relevant shape. biochemical markers have been extremely useful to . pathologists and other plant scientists. though there has been some concern that the outcomes There are three major types of genetic markers: of DNA marker technology as proposed by initial stud. mental stage of the plant (Winter & Kahl. variants of enzymes called isozymes. pulses (Kelly et al. (1) morphological (also ‘classical’ or ‘visible’) mark- ies may not be as effective as first thought. Paterson. trait. Fregene et al. Lee. 2001.. (1997).. growth habits or pigmentation. called ‘molecular breeding’ (Rafalski & Tingey. development and MAS. 1995). 2003.. 1996... Koebner & Summers. QTL analysis. This description A linkage map may be thought of as a ‘road map’ of the is based on whether markers can discriminate between chromosomes derived from two different parents (Pa- homozygotes and heterozygotes (Figure 2). these sizes are estimated from a molecular weight (MW) DNA ladder. there are only two different marker alleles. DNA mark- ers are practically unlimited in number and are not af- fected by environmental factors and/or the develop- mental stage of the plant (Winter & Kahl.. ing genes and QTLs associated with traits of interest. Polymorphic markers are indicated by ar- hybridization-based. 171 plant breeders (Eagles et al. However the advantages and disadvantages of sexual reproduction). 1999. Diagram representing hypothetical DNA markers between classes based on the method of their detection: (1) genotypes A. (a) Example of SSR markers.. ers are either present or absent. terson. For both polymorphic ing with chemicals (ethidium bromide or silver) or markers. Win. These markers are called polymorphic Section II: Construction of linkage maps markers. 1995). 1995. Linkage maps indicate the position and nant markers indicate differences in size whereas dom. Weeden et al. Genes or markers that Table 1. The polymor- (PCR)-based and (3) DNA sequence-based (Gupta phic marker reveals size differences for the marker alleles of the et al. Apart from the use of DNA markers in the construction of linkage maps. 1996a). combination (called crossing-over) during meiosis (i. they have numerous applications in plant breeding such as assessing the level of genetic diver- sity within germplasm and cultivar identity (Baird et al. Polymorphic markers may also be de- scribed as codominant or dominant. erated.. Winter & Kahl. along a highway. are close together or tightly-linked will be transmitted . 2003. 1995). Codomi. Note that these mark- veal genetic differences that can be visualised by us. nucleotide base pairs (bp) are also provided. Codominant markers may have many differ. Jahufer et al. C and D. maps is to identify chromosomal locations contain- leles’. B. DNA markers may be broadly divided into three Figure 1. (b) Examples ter & Kahl. relative genetic distances between markers along chro- inant markers are either present or absent. The most important use for linkage different sized bands on gels) are called marker ‘al. DNA markers are the most widely used type of marker predominantly due to their abundance. These markers are selectively neutral because they are usu- ally located in non-coding regions of DNA. 1997.g. of markers generated by the RAPD technique.e. Joshi et al. They arise from different classes of DNA mutations such as substitution mutations (point mutations)... 1995). rearrange- ments (insertions or deletions) or errors in replication of tandemly repeated DNA (Paterson. 1996a). ent alleles whereas a dominant marker only has two such maps may then be referred to as ‘QTL’ (or ‘ge- alleles. detection with radioactive or colourimetric probes. Strictly mosomes. Weising et al. whereas markers that do not discriminate between genotypes are called monomorphic markers What are linkage maps? (Figure 1). DNA markers are particularly useful if they reveal differences between individuals of the same or dif- ferent species. four genotypes. Essentially... netic’) maps. 1994). thus allowing their analysis in the most commonly used markers are presented in the progeny (Paterson. Henry. 2001. the sizes of these markers in ing a technique called gel electrophoresis and stain. which is analogous to signs or landmarks speaking. 1999. Jones et al. ‘QTL mapping’ is based on the principle It is beyond the scope of this review to discuss that genes and markers segregate via chromosome re- the technical method of how DNA markers are gen.. Often. Markers that do not discriminate between genotypes are called monomorphic markers. and represent a single genetic locus. 1996a). (2) polymerase chain reaction rows. Unlike morphological and biochemical markers. 1997. the different forms of a DNA marker (e. DNA markers may re. 1997. Tanksley polymorphism • Transferable across • Large amounts of DNA required et al.. Huettel et al. 1996).. Morgans (cM) (discussed later). The construction of a linkage map requires a segregat- combination fractions. the reader is encouraged to consult basic textbooks on genetics or quantitative genetics (for example. Markers that have a recombination frequency of 50% are described as ‘unlinked’ and as- sumed to be located far apart on the same chromosome or on different chromosomes. or ‘microsatellites’ • Transferable between of primers Taramino & Tingey (1996) populations • Usually require polyacrylamide electrophoresis Amplified D • Multiple loci • Large amounts of DNA required Vos et al. Comparison between (a) codominant and (b) dominant recombination fractions into map units called centi- markers. The parents selected for the mapping the segregation of markers. which may by used to infer ing plant population (i.. repeats (SSRs)∗ • Robust and reliable labour required for production Powell et al. Mapping functions are used to convert Figure 2.e. Advantages and disadvantages of most commonly-used DNA markers for QTL analysis Molecular Codominant (C) marker or Dominant (D) Advantages Disadvantages References Restriction C • Robust • Time-consuming. Welsh & amplified • Inexpensive • Generally not transferable McClelland (1990). The frequency of recombinant genotypes can be used to calculate re. (2) iden- tification of polymorphism and (3) linkage analysis of together from parent to progeny more frequently than markers. tances between markers can be determined–the lower Population sizes used in preliminary genetic mapping the frequency of recombination between two markers. (1995) fragment Length • High levels of • Complicated methodology Polymorphism (AFLP) polymorphism generated ∗ SSRsare also known as sequence tagged microsatellite site (STMS) markers (Davierwala et al. Linkage maps are con- Genotypes at two marker loci (A and B) are indicated below the gel structed from the analysis of many segregating mark- diagrams. ers. polymorphic • Multiple loci from a single Williams et al. studies generally range from 50 to 250 individuals . Kearsey & Pooni. laborious Beckmann & Soller (1986). the higher the frequency of recombination be- tween two markers. For a more detailed ex- planation of genetic linkage. a population derived from sex- the genetic distance between markers. fragment length • Reliable and expensive Kochert (1994). (1990) DNA (RAPD) primer possible • Small amounts of DNA required Simple sequence C • Technically simple • Large amounts of time and McCouch et al. Winter et al. 2003. In a segregating population. the further away they are situated on a chromosome). 1999). 1999.172 Table 1. there is a mixture Mapping populations of parental and recombinant genotypes. The three main steps of linkage map construction are: (1) production of a mapping population. population will differ for one or more traits of interest. (1989) (RFLP) populations • Limited polymorphism (especially in related lines) Random D • Quick and simple • Problems with reproducibility Penner (1996). the closer they are situated on a chromosome (con- versely. 2001. (1997).. Codominant markers can clearly discriminate between homozygotes and heterozygotes whereas dominant markers do not. By analysing ual reproduction). genes or markers that are located further apart (Fig- ure 3). (1996). Hartl & Jones. the relative order and dis. 2000. Mohapatra et al. (Figure 4).e. mapping pop. produce homozygous or ‘true-breeding’ lines that can Several different populations may be utilized be multiplied and reproduced without genetic change for mapping within a given plant species. species are also polyploid (contain several sets of chro.. The smaller the distance between two markers. disadvantage. This can be observed in a segregating mapping population. Paterson. Diagram indicating cross-over or recombination events between homologous chromosomes that occur during meiosis. each containing a unique combination of chromosomal mosome pairs). cereal that were distinctly different for important traits asso. 2000). 1996a) be used for QTL studies (which is usually the case).g. time to produce. Many cross pollinating plant lines. the sit. If the map will tages (McCouch & Doerge.). Mapping populations used for mapping segments from the original parents. types of mapping populations developed for self Generally in self-pollinating species. Forster et al. barley and wheat). the production of DH populations is only possible in veloped by pair crossing heterozygous parental plants species that are amenable to tissue culture (e. pollinating species. The major ciated with plant persistence and seed yield (Barrett advantages of RI and DH populations are that they et al. In cross pollinating species. F2 populations. 1992). Inbreeding from individual F2 plants uation is more complicated since most of these species allows the construction of recombinant inbred (RI) do not tolerate inbreeding. however larger populations are population type possessing advantages and disadvan- required for high-resolution mapping. species such as rice. in are required. and backcross (BC) populations. Their main advantages are that ulations originate from parents that are both highly ho. because usually six to eight generations mozygous parent (Wu et al. with each occurring.) and ryegrass (Lolium perenne L. Therefore. generation mapping populations were successfully de. F1 of chromosome doubling from pollen grains. trait data the F1 hybrid to one of the parents. which consist of a series of homozygous lines. are the simplest must be collected) before subsequent QTL mapping. (Mohan et al. 1997).. 1995. 173 Figure 3. the smaller the chance of recombination occurring between the two markers. be produced by regenerating plants by the induction folium repens L. derived from F1 hybrids. Doubled haploid (DH) populations may both the cross pollinating species white clover (Tri.. For example. however. then an important point to note is that the mapping pop. derived by crossing ulation must be phenotypically evaluated (i. By analysing the number of recombinants in a population.. recombination between markers G and H should occur more frequently than recombination between markers E and F. This allows for the conduct of replicated . The length of cross pollinating species may be derived from a cross time needed for producing RI populations is the major between a heterozygous parent and a haploid or ho. 2004. it could be determined that markers E and F are closer together compared to G and H. Gametes that are produced after meiosis are either parental (P) or recombinant (R). they are easy to construct and require only a short mozygous (inbred). 1993. In many F2 1: 2:1 (AA:Aa:aa) 3:1 (B :bb) cases.174 Figure 4. polymorphic markers). Therefore. trials across different locations and years. 1994). . Thus both The choice of DNA markers used for mapping may de- RI and DH populations represent ‘eternal’ resources pend on the availability of characterised markers or the for QTL mapping. 1994). It is critical viations from expected ratios can be analysed using that sufficient polymorphism exists between parents in order to construct a linkage map (Young. 1993. 1994). if pos- 1996a. doubled haploid 2003. laboratories for further linkage analysis and the Once polymorphic markers have been identified. Collard et al. This is known as marker ‘genotyping’ of the population. nant markers are presented in Table 2.. Young. Yu & Nguyen. ensuring that they must be screened across the entire mapping pop- all collaborators examine identical material (Paterson. Joshi & Nguyen. Diagram of main types of mapping populations for self-pollinating species. mapping in inbreeding species generally requires the Population type Codominant markers Dominant markers selection of parents that are distantly related. DNA must be extracted from each individual of the mapping population when DNA Identification of polymorphism markers are used. sible). The The second step in the construction of a linkage map expected segregation ratios for codominant and domi- is to identify DNA markers that reveal differences be. Significant de- tween parents (i. cross pollinating species possess higher levels of lation types DNA polymorphism compared to inbreeding species. seed from individual appropriateness of particular markers for a particular RI or DH lines may be transferred between different species.. Expected segregation ratios for markers in different popu- eral. ulation. including the parents (and F1 hybrid.e. Examples of DNA markers screened across different populations are shown in Figure 5. In gen- Table 2. parents that provide adequate polymorphism are Backcross 1:1 (Cc:cc) 1:1 (Dd:dd) selected on the basis of the level of genetic diversity Recombinant inbred or 1:1 (EE: ee) 1:1 (FF:ff) between parents (Anderson et al. Furthermore. addition of markers to existing maps. 1993). Linkage be- identifying polymorphic markers is more complicated tween markers is usually calculated using odds ratios (Ripol et al. This ratio polyploid species can be of great benefit in developing is more conveniently expressed as the logarithm of the maps for polyploid species.. . 1000:1) than no linkage (null hypothesis). 1992). the ratio of linkage versus no linkage). A general method for the mapping of cally used to construct linkage maps. 1992).. A LOD value of polyploid species is based on the use of single-dose 3 between two markers indicates that linkage is 1000 restriction fragments (Wu et al. 1993a) volves coding data for each DNA marker on each indi. markers will segregate in Although linkage analysis can be performed manu- a Mendelian fashion although distorted segregation ra. Note that dominant markers cannot discriminate between heterozygotes and one homozygote genotype in F2 populations. computer In some polyploid species such as sugarcane. ally for a few markers. which vidual of a population and conducting linkage anal. Xu et al.e. 1999). programs are required for this purpose. Generally. 2002. JoinMap is an- ysis using computer programs (Figure 6). Lincoln et al. 1999. times more likely (i.. LOD values of >3 are typi- Wu et al. of markers that are used to construct maps. diploid relatives ratio.. Hypothetical gel photos representing segregating codominant markers (left-hand side) and dominant markers (right-hand side) for typical mapping populations. However. are freely available from the internet. 1987. age maps (Stam. 1992). Missing other commonly-used program for constructing link- marker data can also be accepted by mapping programs. LOD score (Risch.e. it is not feasible to manually tios may be encountered (Sayed et al.. maker/EXP (Lander et al. and is called a logarithm of odds (LOD) value or do not exist for all polyploid species (Ripol et al. chi-square tests. LOD values may be lowered in order to detect a greater level of linkage or to place additional Linkage analysis of markers markers within maps constructed at higher LOD val- ues. Commonly used software programs include Map- The final step of the construction of a linkage map in.. 2001). and MapManager QTX (Manly et al.. Codominant markers indicate the complete genotype of a plant. The segregation ratios of markers can be easily understood by using Punnett squares to derive population genotypes. The mapping of diploid relatives of (i.. 175 Figure 5. analyze and determine linkages between large numbers 1997).. Young. Ideally.. A typical output of a linkage map is shown over the chromosome. Construction of a linkage map based on a small recombinant inbred population (20 individuals). The first parent (P1 ) is scored as an ‘A’ whereas the second parent (P2 ) is scored as a ‘B’. 1994). Coding of marker data varies depending on the type of population used. A difficulty The accuracy of measuring the genetic distance associated with obtaining an equal number of linkage and determining marker order is directly related to the groups and chromosomes is that the polymorphic number of individuals studied in the mapping popu- markers detected are not necessarily evenly distributed lation. In addition to into ‘linkage groups. This linkage map was constructed using Map Manager QTX (Manly et al. 2001.’ which represent chromosomal the non-random distribution of markers. the frequency segments or entire chromosomes. Referring to the of recombination is not equal along chromosomes road map analogy. linkage groups represent roads and (Hartl & Jones. markers represent signs or landmarks. mapping populations should consist of . 1996a).176 Figure 6. but clustered in some regions in Figure 7. 2001) using the Haldane mapping function. Linked markers are grouped together and absent in others (Paterson. the relationship between genetic and physical dis- combination occurring during meiosis. Hypothetical ‘framework’ linkage map of five chromosomes (represented by linkage groups) and 26 markers. ence between crossover events (Hartl & Jones. and the ever. the map distance equals the recombi. 1992. 2000. crossing-over are not linearly related (Hartl & Jones. curs more frequently or less frequently. Furthermore. How- currence of adjacent recombination events. this relationship does not apply for map distances that are greater than 10 cM Principle of QTL analysis (Hartl & Jones.. Young. the framework map should also consist of anchor markers that are present in several maps. However. The greater the of the plant species (Paterson. 177 Figure 7.’ which 1996a). Ma et al. 2001). 1994). 2001. a framework map should consist of evenly spaced markers for subsequent QTL analysis. If possible. 1996). 1996a).. 1994). For example. a linkage map is measured in terms of the frequency Tanksley et al. Yao et al. Genetic distance and mapping functions It should be noted that distance on a linkage map is not directly related to the physical distance of DNA be- The importance of the distance between genes and tween genetic markers.. Mapping functions are required to convert are chromosomal regions in which recombination oc- recombination fractions into centiMorgans (cM) be. Distance along tance varies along a chromosome (Kunzel et al. Kearsey & Pooni... 1996). 2001. but depends on the genome size markers has been discussed earlier. so that they can be used to compare regions between maps. Section III: QTL analysis nation frequency. respectively cause recombination frequency and the frequency of (Faris et al. Kearsey & Pooni. 2002). distance between markers. which assumes no interfer- maps (Young. When map distances are small (<10 cM). Two commonly used mapping functions are the Kosambi mapping function. 2001. the greater the chance of re. Ideally. which Identifying a gene or QTL within a plant genome is assumes that recombination events influence the oc. QTL analysis can be used to divide the haystack . like finding the proverbial needle in a haystack. there of recombination between genetic markers (Paterson. are recombination ‘hot spots’ and ‘cold spots. 2000. a minimum of 50 individuals for constructing linkage Haldane mapping function. Methods to detect QTLs A logical question that may be asked at this point is ‘why does a significant P value obtained for differences Three widely-used methods for detecting QTLs are between mean trait values indicate linkage between single-marker analysis. no significant A significant difference between phenotypic means of differences between means of the genotype groups will the groups (either 2 or 3). .g. there will be no tion the mapping population into different genotypic significant difference between means of the genotype groups based on the presence or absence of a particu. Principle of QTL mapping (adapted from Young. of variance (ANOVA) and linear regression. the lower the chance for recombination between marker and QTL. the marker and QTL. The closer a marker is from a QTL. Marker H is unlinked to a QTL because there is no significant difference between means. 1996). the lower the chance 1993). 1993. Based on the results in this diagram. therefore. analysis with the tightly-linked marker will be significantly dif. there is independent segregation of the genotype of markers. simple interval mapping and marker and QTL?’ The answer is due to recombination. Young.05) to the mean of the group without the simple terms. be detected. The statistical methods ited together in the progeny. indicates that the marker locus being used to partition the mapping population is linked to a QTL controlling the trait (Figure 8). Unlinked markers located far differences exist between groups with respect to the apart or on different chromosomes to the QTL are ran- trait being measured (Tanksley. Tanksley. 1996). The closer the marker is to the QTL of interest. tem and type of population. QTL analysis is based on the principle marker (Figure 9). and the mean of the group used for single-marker analysis include t-tests. groups based on the presence or absence of the loosely- lar marker locus and to determine whether significant linked marker (Figure 9). Markers that are linked to a gene or QTL controlling a particular trait (e. the QTL and marker will be usually be inher. ysis’) is the simplest method for detecting QTLs as- Therefore. In this situation. plant height) will indicate significant differences when the mapping population is partitioned according to the genotype of the marker. Linear Figure 8. depending on the marker sys. Single-marker analysis (also ‘single-point anal- of recombination occurring between marker and QTL. Marker E is linked to a QTL because there is a significant difference between means. In ferent (P < 0. When a marker is loosely-linked or of detecting an association between phenotype and unlinked to a QTL. 1998. composite interval mapping (Liu. domly inherited with the QTL. Markers are used to parti. sociated with single markers.178 in manageable piles and systematically search them. 1989). This causes the magnitude of the effect statistically more powerful compared to single-point of a QTL to be underestimated (Tanksley. computer programs to perform single-marker analysis ficient of determination (R2 ) from the marker explains (Manly et al. 1989. 2001. Single-marker analysis of markers associated with QTLs using QGene (Nelson.0001 58 variation explained by the QTL (R2 ) (Table 3). Table 3. The results from single-marker analysis are usually Chromosome or presented in a table. 179 Figure 9. Diagram indicating tight and loose linkage between marker and QTL. 1998).0230 26 times. This is be. Many use of a large number of segregating DNA markers covering the entire genome (usually at intervals less than 15 cM) may minimize both problems (Tanksley. The use of linked mark- marker. 1993). This method does not require a complete use of linkage maps and analyses intervals between linkage map and can be performed with basic statistical adjacent pairs of linked markers along chromosomes software programs.0001 91 probability values. E 2 <0. regression is most commonly used because the coef. Liu. 1997) 1993). which indicates the chromosome Marker linkage group P value R2 (if known) or linkage group containing the markers. 1997). H 2 0. Markers that are tightly-linked to a QTL (Marker E) are usually inherited with the QTL in the progeny. Markers that are only loosely-linked to a QTL (Marker H) are randomly inherited together. the major disadvantage simultaneously. the phenotypic variation arising from the QTL linked The simple interval mapping (SIM) method makes to the marker. ers for analysis compensates for recombination be- cause recombination may occur between the marker tween the markers and the QTL.5701 2 QGene and MapManager QTX are commonly used . Nelson. (b) Gametes in population. and is considered and the QTL. Some- G 2 0. The analysis (Lander & Botstein. (a) Recombination events (indicated by crosses) occurs between QTL and marker loci. However. and the percentage of phenotypic F 2 0. the allele size of the marker is also reported.. instead of analyzing single markers with this method is that the further a QTL is from a (Lander & Botstein. the less likely it will be detected. 2001) 1994). The output indicates that the most likely position for the QTL is near marker Q (indicated by an arrow). Jansen & Stam.180 researchers have used MapMaker/QTL (Lincoln et al. 1997). the phenotypic values of the population and PLABQTL (Utz & Melchinger. be calculated by: LRS = 4. The results of the test statistic for Before permutation tests were widely accepted SIM and CIM are typically presented using a logarith. 1993b) and QGene (Nelson. based on the level of false positive marker-trait associ- ers. formed using permutation tests (Churchill & Doerge.0) was usually chosen as the significance tween LOD scores and LRS scores (the conversion can threshold. Figure 10. Zeng. 1997). Briefly.0 to 3. to a linkage map. 2002. 1996) to perform are ‘shuffled’ whilst the marker genotypic values are CIM. a LOD score of between 2. 1998). as an appropriate method to determine significance mic of odds (LOD) score or likelihood ratio statistic thresholds. especially when linked QTLs are involved. MapManager QTX (Manly et al. 1994. QTLs are located with respect ations.6 × LOD) (Liu. There is a direct one-to-one transformation be. The determina- ping. 1993. (Figure 10). all marker-trait associations are bro- ken) and QTL analysis is performed to assess the level of false positive marker-trait associations (Churchill Understanding interval mapping results & Doerge. as ‘real’ (i. statistically significant). Haley & Andersson. The best flanking markers for this QTL would be Q and R.g. Hypothetical output showing a LOD profile for chromosome 4.0 (most (LRS). This method age map. 1994. A typical output from interval includes additional genetic markers in the statistical mapping is a graph with markers comprising linkage model in addition to an adjacent pair of linked markers groups on the x axis and the test statistic on the y axis for interval mapping (Jansen.. Hackett. 2001). These LOD or LRS profiles are used to identify the More recently. The main advantage of CIM The peak or maximum must also exceed a specified is that it is more precise and effective at mapping QTLs significance level in order for the QTL to be declared compared to single-point analysis and interval map. 1994. which is the position where the highest combines interval mapping with linear regression and LOD value is obtained.. The dotted line represents the significance threshold determined by permutation tests.e. 1993. . held constant (i. 1994). In other words.. commonly 3. This process is then repeated (e. Many tion of significance thresholds is most commonly per- researchers have used QTL Cartographer (Basten et al. composite interval mapping (CIM) most likely position for a QTL in relation to the link- has become popular for mapping QTLs. to conduct SIM.e. 500 or 1000 Interval mapping methods produce a profile of the times) and significance levels can then be determined likely sites for a QTL between adjacent linked mark. tected for traits that segregate between the parents used 2002). It should also be noted that QTLs can only be de- 2002.. 181 Reporting and describing QTLs detected flanking markers is that selection based on two mark- from interval mapping ers should be more reliable than selection based on a single marker. et al.. Pilet-Nayel et al. in or- angles are usually the region that exceeds the signifi. a pair of markers study. 2003a.. 2003. QTLs known as ‘flanking’ markers. 2002. A major QTL for height was detected on chromosome 2. Hypothetical QTLs were detected on chromosomes 2. QTL mapping of height and disease resistance traits. 3.. .. QTL – is also reported in a table. 2003. 2002). Two major QTLs for disease resistance were detected on chromosomes 4 and 5 whereas a minor QTL was detected on chromosome 3 (adapted from Hartl & Jones. 4 and 5. chance of recombination between a single marker and age maps (for example: Beattie et al. Pilet-Nayel et al.. is that there is a much lower chance of recombina- dicating the most closely linked markers in a table tion between two markers and QTL compared to the and/or as bars (or oval shapes or arrows) on link. Hittalmani et al. Jampatong et al. McCouch & Doerge. several criteria may be used for phenotypic eval- – the most tightly-linked markers on each side of a uation of a single trait (Flandez-Galvez et al. The reason for the increased reliability The most common way of reporting QTLs is by in.. Usually. to construct the mapping population. The chromosomal regions represented by rect. Therefore. George QTL. 1995. 1988. 2001). these markers are Paterson et al. The reason for reporting that are detected in common regions (based on different Figure 11. der to maximize the data obtained from a QTL mapping cance threshold (Figure 11).. If detected. However. Lander & mapping population (derived from two specific par- Kruglyak (1995) proposed this classification in order to ents) and the types of markers used. since the num- be available for marker genotyping. QTLs actually occur within confidence inter... Pilet-Nayel et al. 1993). especially for marker spacing of 20 or even 50 cM. ported that the power of detecting a QTL was virtually times. and can be easily applied within some mapping 2003.. and (3) highly. ent traits can be located on a single map (Beattie et al. 2002.g.182 criteria for a single trait) are likely to be important QTLs region on both sides of a QTL peak that corresponds to for controlling the trait. (1993) re- minor QTLs will usually account for <10%. the boundaries of each are defined position at which the highest LOD or LRS score is by a set of core RFLP markers’ (Polacco et al. software programs such as MapManager QTX (Manly 2001.. 2001). the same set of lines of the map. be. Gardiner et al. 1995). et al. an individual QTL may also be equate. 1996). Visscher et al. 2002. Therefore.’ which is determined by finding the 2003). (2) significant.. 2003.g. 2003. major QTLs may refer to QTLs that are stable the same for a marker spacing of 10 cM as for an in- across environments whereas minor QTLs may refer to finite number of markers. Making comparisons between maps In more formal terms. and preliminary genetic mapping studies gen- described as ‘major’ or ‘minor’.. respectively.. and only slightly decreased QTLs that may be environmentally sensitive. (Manly et al. This for resampling–is another method to determine the con- is advantageous because QTLs controlling the differ. Some. may be referred to as ‘bins’. 2002). this depends on the genome size by a QTL (based on the R2 value): major QTLs will ac. Khairallah et al. fold’) map consisting of evenly spaced markers is ad- In general terms.. Karakousis et al. ever. screening for resis. are highly polymorphic in mapping populations are there is a warning regarding the reliability of sugges. order to correlate information from one map to another. reports QTL mapping results with this classification Flandez-Galvez et al. common anchor markers have been incorporated into vals. Consensus maps are produced by combining . How.. a decrease of 1 LOD score (Hackett. The simplest is the ‘one-LOD ‘consensus’ maps (Ablett et al.. 1998. in levels of 5 and 0. Furthermore. a relatively sparse ‘framework’ (or ‘skeletal’ or ‘scaf- tance to necrotrophic fungal pathogens). Number of markers and marker spacing cause the parents may only segregate for one trait of interest. called ‘anchor’ (also ‘core’ markers). 1997. The mapping program MapManager QTX ers are typically SSRs or RFLPs (Ablett et al. 2002).. more markers are required for mapping count for a relatively large amount (e. this is not always possible. Common markers that at random in a QTL mapping study (in other words. Lindhout. 1997). of the species. 2002).1%. for QTLs that are associated with disease resistance (Li et al. they can be aligned together to produce vals can be calculated. This definition is based erally contain between 100 and 200 markers (Mohan on the proportion of the phenotypic variation explained et al. Marquez-Cedillo et al. whereas a sugges. Specific groups of anchor markers. There are several ways in which confidence inter. 1998. Lander & Mapping populations may also be constructed Botstein. there that “true hints of linkage” were not missed.. that are located in close proximity to each other in specific genomic re- Confidence intervals for QTLs gions. tive QTL is one that would be expected to occur once common markers are required. Anchor mark- tive QTLs). fidence interval of QTLs (Liu. for many parental genotypes used to construct mapping populations. or semi-destructive bioassays (e.. Darvasi et al. There is no absolute value for the number of DNA ping population used for phenotypic evaluation must markers required for a genetic map. and are defined as ‘10–20 cM regions Although the most likely position of a QTL is the map along chromosomes.. Tar’an et al.. support interval. All linkage maps are unique and are a product of the significant (Lander & Kruglyak. Bins are used to integrate maps. which may be difficult with completely chromosomes in the organism. different maps.. >10%) and in species with large genomes.. and subsequent ber of markers varies with the number and length of QTL analysis. 1989). ‘Bootstrapping’ – a statistical method based on parents that segregate for multiple traits. 2001). Even if the same “avoid a flood of false positive claims” and also ensure set of markers is used to construct linkage maps. Serquen et al. Significant is no guarantee that all of the markers will be poly- and highly-significant QTLs were given significance morphic between different populations. 2003b. 2001. QTLs may be classified as: (1) suggestive. For detection of QTLs. mapping study. genera or higher The main sources of experimental error are mis- taxonomic divisions is referred to as comparative map... Previous tings) can be used to improve the accuracy of QTL map- linkage maps may provide an indication of which mark. 2002. Un- different seasons and years) may enable the researcher fortunately. Com. because QTL map- Environmental effects may have a profound influ. Such confirmation clude the magnitude of the effect of individual QTLs. and genes within and between species. Replicated regions) and in predicting the locations of QTLs in dif. ping studies should be independently confirmed or ver- Genetic properties of QTLs controlling traits in. 1993). environmental effects. Darvasi et al. as well as provide an indication of 1994. 1994). 2002. It involves analysing the evaluation. Utz et al. a consensus map can indicate QTLs with smaller effects (Haley & Andersson. constructed from differ. 1998. the more accurate the map- (with evenly spaced markers) or targeted (or localized) ping study and the more likely it is to allow detection of mapping. RI or DH populations are ideal for resistance (Li et al. ping by reducing background ‘noise’ (Danesh et al.. linkage maps (Hackett. 1998. 1993). 2003). 2002. . for ascochyta blight resistance in chickpea (Flandez- Galvez et al.. larger population sizes QTLs that are closely-linked (approximately 20 cM or may be used. tions constructed from the same parental genotypes or low the significance threshold of detection. evolutionary relationships between taxa. 2002). Hittalmani of the need to confirm results. Tanksley. 1991b.. fects and confidence intervals of the locations of QTLs The study of similarities and differences of markers (Beavis. phenotypic measurements or the use of clones (via cut- ferent mapping populations (Young. 2002. 183 or merging different maps. funding and time.. Some notable exceptions are the con- Paterson et al. bacterial brown spot in common Factors influencing the detection of QTLs bean (Jung et al. and possibly a lack of understanding ing trait(s) of interest (George et al... 2003. takes in marker genotyping and errors in phenotypic ping (Paterson et al. QTL map- population size and experimental error. some recent studies have less) will usually be detected as a single QTL in typical proposed that QTL positions and effects should be eval- population sizes (<500) (Tanksley. Price & Courtois. The accuracy of pheno- served marker order is referred to as ‘synteny’. An increase in population size pro- ing a QTL. soybean (Fasoula et al. and thus be used to identify more tightly vides gains in statistical power. studies (referred to as ‘replication studies’ by Lander Only QTLs with sufficiently large phenotypic effects & Kruglyak. Genotyping errors and missing data can extent of the conservation between maps of the order affect the order and distance between markers within in which markers occur (i. 2002). 1991a). due to constraints such as lack of research to investigate environmental influences on QTLs affect. The main ones are genetic proper- ties of QTLs that control traits. 1997.e. con. Haley & Andersson. QTLs with small effects may fall be.. Such consensus maps can be the size of the population used in the mapping study. Ideally. 1993).. 1995) may involve independent popula- will be detected. 1999). There are many factors that influence the detection of QTLs segregating in a population (Asins. 1995).g. 2003a). Another closely-related genotypes used in the primary QTL genetic property is the distance between linked QTLs. As dis. 2001) and bud blight resistance in these purposes. Furthermore. Jampatong et al.. 2003). due to the factors described above. collinear markers). For example. A reliable QTL map can only linkage maps (or localized maps of specific genomic be produced from reliable phenotypic data. which markers are located in a specific region contain. Sometimes. The most important experimental design factor is ent genotypes. fects (Melchinger et al. Experi. ified (Lander & Kruglyak. comparative mapping may reveal been conducted in both field and glasshouse trials. uated in independent populations. together. Some thorough stud- linkage groups and the order of markers within linkage ies include those where phenotypic evaluations have groups. firmation of QTLs associated with root-knot nematode cussed previously. Furthermore. 1997). power of QTL detection and a large bias of QTL ef- ments that are replicated across sites and over time (e. Confirmation of QTL mapping Tanksley. ers are polymorphic. rarely confirmed. QTL mapping studies are et al... ping based on typical population sizes results in a low ence on the expression of quantitative traits.. 2000). Lindhout. and downy mildew resistance in pearl millet (Jones et al. 1993). typic evaluation is of the utmost importance for the ac- parative mapping may assist in the construction of new curacy of QTL mapping. estimates of gene ef- linked markers. extremely useful for efficiently constructing new maps The larger the population. especially if resources are limited. but the method may also be used to iden- lines (NILs). the individuals selected for extreme phenotypic values will usually not represent extreme phenotypic values Short cuts for gene tagging for other traits) (Tanksley. linked to a gene or QTL of interest (Figure 12). the effects of QTLs genotyping is typically used when growing and phe- can be confirmed.. ‘scaffold’ linkage map) that covers all chromosomes . Lander & Botstein. and will there- ticular disease).g. By geno- of backcrossing. It should be 1989. Both methods require mapping populations. interval mapping methods must be used (Lander may be very expensive. resolution mapping. The are generally preferred for BSA. Linkage map construction noted that in order to produce a NIL containing a target and QTL analysis is performed using only the individ- gene. duce a comprehensive ‘framework’ (also ‘skeletal’ or 1999).. The entire population is then genotyped with these poly. However. leaf rust resistance in barley says.g. 7). these two bulks should differ for not adequately tested before use in MAS programs may a trait of interest (e. The final extreme analysis’ or ‘trait-based marker analysis’) in- BC7 will contain practically all of the recurrent parent volves selecting individuals from a population that rep- genome except for the small chromosomal region con. that can gener- The F1 hybrid is then backcrossed to the recurrent par. Briefly. Furthermore. 1993).. the markers identified in in specific chromosomal regions (Michelmore et al. not efficient in determining the effects of QTLs and bean (Glover et al. 2003). resent the phenotypic extremes or tails of the trait being taining a gene or QTL of interest. 2001). preliminary genetic mapping studies are seldom suit- 1991). ent to produce a first backcross generation (BC1).g. BC1 is then repeatedly backcrossed to the recurrent Selective genotyping (also known as ‘distribution parent for a number of generations (e. be- The construction of linkage maps and QTL analysis cause the phenotypic effects would be grossly overesti- takes a considerable amount of time and effort. Markers are screened across the two bulks. Examples of studies utilizing NILs notyping individuals in a mapping population is easier to confirm QTLs include agronomic traits in tomato and/or cheaper than genotyping using DNA marker as- (Bernacchi et al. Zhang et al. single- point analysis cannot be used for QTL detection. 1998).184 Another approach used to confirm QTLs has been BSA is generally used to tag genes controlling sim- to use a specific type of population called near isogenic ple traits. an elite cultivar). 1993. parent (e. ate multiple markers from a single DNA preparation.. 1989). Two ‘short-cut’ Section IV: Towards marker-assisted selection methods used to identify markers that tag QTLs are bulked segregant analysis (BSA) and selective geno.g. and comparing mean trait values of particular mapping study can be significantly reduced. can be obtained by selfing the BC7 plant. ‘High-throughput’ or ‘high-volume’ marker interest) to a recurrent parent (e.. resistant vs. all loci are fore be useless. and mated. High-resolution mapping of QTLs morphic markers and a localized linkage map may be generated. ing and possibly further development. By making DNA bulks. Therefore. susceptible to a par. two pools or ‘bulks’ of DNA samples able for marker-assisted selection without further test- are combined from 10–20 individual plants from a seg. nematode resistance in soy. validation of markers and possibly Polymorphic markers may represent markers that are marker conversion (discussed below). NILs are created by crossing a donor tify markers linked to major QTLs (Wang & Paterson. Generally. alternative methods & Botstein. 2001). a phenotype is selected on the the genotype of a marker BSA is a method used to detect markers located (see Section V). The disadvantages of this method are that it is (Van Berloo et al. not be reliable for predicting phenotype. Homozygous F2 lines analysed (Foolad & Jones. This enables QTL analysis to be performed The preliminary aim of QTL mapping is to pro- and the position of a QTL to be determined (Ford et al. except for the region containing the gene velopment of markers for use in MAS includes: high- of interest. By genotyping NILs with important typing a subsample of the population. 2004) and phosphorus uptake in that only one trait can be tested at a time (because rice (Wissuwa & Ae. wild parent possessing a specific trait of 1994). Marker-assisted selection (MAS) is a method whereby typing. the steps required for the de- randomised. the costs of a markers. Markers that are regating population. techniques such as RAPD or AFLP. Selective NIL lines with the recurrent parent. that can save time and money would be extremely use- ful. the gene has to be selected for during each round uals with extreme phenotypes (Figure 13).. assisted selection (at least <5 cM but ideally <1 cM 2001. 2003). 185 Figure 12. 2003. Therefore.. (Adapted from Langridge et al. map. Chunwongse (Michelmore. on the size of the population used to construct the Mohan et al. tightly-linked markers can be identified. because even the closest markers flank... this process AFLP) are usually preferred for increasing marker is termed ‘high-resolution mapping’ (also ‘fine map.g. the sizes of segregating pop- There is no universal number for the appropriate ulations being used are too small to permit high- population size required for high-resolution mapping. Such markers are then used to genotype the entire mapping population and QTL analysis performed. the extent away from the gene) and also to discriminate between a to which framework maps can be saturated depends single gene or several linked genes (Michelmore. two bulks (B1 and B2 ) are made from individuals displaying extreme phenotypic scores. In many cases. since smaller populations have . Tanksley et al.. viduals to resolve QTLs to distances between flanking ing a QTL may not be tightly linked to a gene of interest markers of <1 cM (Blair et al. resolution mapping. density (Figure 14). 1991). The preparation of DNA bulks for a simple disease resistance trait (a) and a quantitative quality trait (flower colour) (b). population sizes that have been used for that control traits of interest. 1995). to specific chromosomal regions (Campbell et al. Giovannoni et al. thus reducing the The mapping of additional markers may saturate reliability and usefulness of the marker. 1997). In both cases.. can occur between a marker and QTL.. This means that recombination et al. 1995.. High-throughput marker techniques population sizes and a greater number of markers. 1997. (c) Polymorphic markers (indicated by arrows) that are identified between bulks may represent markers that are linked to genes or QTLs controlling the traits. By using larger framework maps. Li et al.) evenly in order to identify markers flanking those QTLs However. There are several more high-resolution mapping have consisted of >1000 indi- steps required.. more that generate multiple loci per primer combination (e. 1995. 2001. Bulked-segregant analysis may ping’). high-resolution mapping of QTLs also be used to identify additional markers linked may be used to develop reliable markers for marker. However. RAPDs) and when Sharp et al. there is no guarantee that rated into a high-resolution map. 2001. RFLPs or AFLPs). Li et al. Spielmeyer 1993). and subsequent linkage and QTL analysis.. In other words. 2000). especially for complex traits such NILs and the recurrent parent should represent markers as yield (Reyna & Sneller. 2003. et al. 2001).186 Figure 13.g. 2001).. The entire population is phenotypically evaluated for a particular trait (e.g. problems of reproducibility (e. Selective genotyping.. especially when the popu- Validation of markers lations originate from distantly related germplasm (Yu et al. fewer recombinants than larger populations (Tanksley. However. Jung et al. Sharp Marker conversion et al... 2003). Even when a single that are linked to the target gene and can be incorpo.. 2001.g. Some studies have warned of the dan- High-resolution maps of specific chromosomal re. they should reveal polymorphism in differ- effectiveness in determining the target phenotype in ent populations derived from a wide range of different independent populations and different genetic back. 1999. disease resistance). the marker technique is complicated.. 2003).. gene controls a particular trait. Markers that are polymorphic between ing environments. grounds..... time-consuming Markers should also be validated by testing for the or expensive (e. DNA markers identified in one population will be use- ful in different populations. 2001. Langridge et al.. parental genotypes (Langridge et al. For markers to be most useful in breeding Generally. 2001). Collins et al. markers should be validated by testing their programs. marker validation involves testing the reliability of markers to predict phenotype. There are two instances where markers may need to be This indicates whether or not a marker could be used converted into other types of markers: when there are in routine screening for MAS (Ogbonnaya et al. important genotypes (Sharp et al. The problem of presence of the marker on a range of cultivars and other reproducibility may be overcome by the development . which is referred to as ‘marker validation’ (Cakir et al. ger of assuming that marker-QTL linkages will remain gions may also be constructed by using NILs (Blair in different genetic backgrounds or in different test- et al. 2001. 2001). 2003. only individuals representing the phenotypic extremes from the mapping population are selected for marker genotyping. 1999. High-resolution linkage mapping. STS markers cost of utilizing several QTLs. Theoretically. or sequence-tagged sites (STSs) derived by cloning and sequencing specific RAPD markers (Jung et al. They detect a single locus and may be codominant (Paran & Michelmore. 1993). 2001). how many QTLs are typically selected for MAS?” 1999). 187 et al. 2003. • selecting for traits with low heritability • testing for specific traits where phenotypic evalua- tion is not feasible (e.. Even Section V: Marker-assisted selection selecting for a single QTL via MAS can be beneficial in plant breeding. between Q and R on chromosome 4) could be useful for MAS. quarantine restrictions may of sequence characterised amplified regions (SCARs) prevent exotic pathogens to be used for screening). Witcombe & Virk. Tanksley. 1993). typically used (Ribaut & Betran. and W). The advantages of MAS include: • time saving from the substitution of complex field trials (that need to be conducted at particular times of year or at specific locations. although there have been reports of up to 5 QTLs being introgressed into tomato via MAS (Lecomte et al. • avoid the transfer of undesirable or deleterious genes ers. less time-consuming and cheaper. 1999. QTLs could be used for MAS. or are technically complicated) with molecular tests.. which often contain large numbers (Ribaut & Betran. • selection of genotypes at seedling stage. all markers that are tightly linked to verted from RFLP or AFLP markers is technically sim. plant breeders typically work with hundreds or even thousands of populations. or STS markers (Lehmensiek et al. Young. only markers that may also be transferable to related species (Brondani are tightly linked to no more than three QTLs are et al. this is of particular relevance when (e. However. Furthermore. 1997..g. (Ribaut & Betran. 1993). the introgression of genes from wild species is in- A bulked-segregant analysis approach can be applied to target spe- cific chromosomal regions as shown on chromosome 5 (between V volved). 1999. SCAR markers are ro.. Weeden all QTLs selected for MAS should be stable across . • gene ‘pyramiding’ or combining multiple genes si- Figure 14.g. Selection of QTLs for MAS bust and reliable. 1994). 1999). Paran & Michelmore. Additional markers multaneously. Moreover. breeders may use specific DNA marker alleles as a diagnostic tool to identify plants carrying the genes or QTLs (Fig- ure 15) (Michelmore. Once markers that are tightly linked to genes or QTLs of interest have been identified. have been utilised to ‘fill in the gaps’ between the anchor mark. RFLP One commonly asked question is that “since quanti- and AFLP markers may also be converted into SCAR tative traits are controlled by at least several QTLs. 1995. 1996). The use of PCR-based markers that are con. due to the pler. • elimination of unreliable phenotypic evaluation as- sociated with field trials due to environmental ef- fects. 2003). The identification of additional markers in the vicinity of QTLs (‘linkage drag’. prior to field evaluation of large numbers of plants. nent of plant breeding (Ribaut & Betran. ‘Marker-assisted selection’ (also ‘marker-assisted breeding’ or ‘marker-aided se- lection’) may greatly increase the efficiency and effec- tiveness in plant breeding compared to conventional breeding methods... Lem & Lallemand. 2001. 1999.. Shan et al. 2004). such a QTL should account for the Selecting plants in a segregating progeny that contain largest proportion of phenotypic variance for the trait appropriate combinations of genes is a critical compo. Ribaut et al. . a robust marker has been developed for a major QTL controlling disease resistance (indicated by the arrow). BC6 99. Ribaut & Betran. large initial cost in their development. An estimate for 1999). An BC5 98. it typically takes to conventional plant breeding varies considerably be. In other situations. Generation parent genome (%) veloped for MAS. crosses.8 therefore using markers may be cheaper and preferable BC4 96. (2003) indicated that the genome. 2002. Yu et al. A susceptible (S) parent is crossed with a resistant (R) parent and the F1 plant is self-pollinated to produce a F2 population.g. Young. it is cheaper than conventional meth- BC1 75. 1998. The notypic evaluation. phenotypic BC2 87. Some studies involving markers for disease Recurrent resistance have shown that once markers have been de. environments (Hittalmani et al. Dreher et al. often not reported. Percentage of recurrent parent genome after backcrossing expensive assays. field/glasshouse and labour costs. The theoretical proportion of the recurrent cost-effectiveness needs to be considered on a case by parent genome after n generations of backcrossing is case basis. method of phe. 2003). 1999. In this diagram. 2000 F2 plants) derived from a single cross and may use populations derived from hundreds or even thousands of crosses in a single year. phenotypic screening may require time-consuming and Table 4. backcross generation are presented in Table 4.040 (Langridge et al. 2003. phenotypic screening is cheaper percentages shown in Table 4 are only achieved with compared to marker-assisted selection (Bohn et al. the percentages are usually lower in 2001. Cost/benefit analysis of MAS Marker-assisted backcrossing The cost of using ‘tools’ in breeding programs is a ma- jor consideration. This is important because plant breeders typically use very large populations (e. The In some cases. the cost to develop a single marker was AUD $ 100.5 evaluation may be time-consuming and/or difficult and BC3 93. in other cases..2 is that while markers may be cheaper to use. large populations. Dreher et al.188 Figure 15. 6–8 backcrosses to fully recover the recurrent parent tween studies... assuming an infinite population size). there is a .. 2001). The cost of using MAS compared Using conventional breeding methods. Factors that influence the cost of utilizing given by: (2n+1 − 1)/2n+1 (where n = number of back- markers include: inheritance of the trait. and the use of markers will then be preferable.4 important consideration for MAS. By using a marker to assist selection. MAS scheme for early generation selection in a typical breeding program for disease resistance (adapted from Ribaut & Hoisington. Ribaut & Betran. plant breeders may substitute large field trials and eliminate many unwanted genotypes (indicated by crosses) and retain only those plants possessing the desirable genotypes (indicated by arrows)... percentages of recurrent parent recovery after each and the cost of resources. 2000). Note that 75% of plants may be eliminated after one cycle of MAS. However.0 ods (Yu et al. 1999). 2000).9 (Dreher et al. and in the last 15 years considerable progress has to conventional breeding in the short term.. considerable time savings can be made by and more innovative and efficient strategies to incorpo- using markers compared to conventional backcrossing. (Young. Although the average percentage of the recurrent parent genome is 75% (for the entire BC1 population). rate MAS within plant breeding programs. 1999). This process is called have not been reliable in predicting the desired phe- marker-assisted backcrossing. 2000) computer simulations of recurrent parent genome (RPG) recovery using marker-assisted backcrossing (MAB) and conventional backcrossing. 1999).. 2000). 2003). from other chromosomes (i. The use of markers can reduce the number of generations required to achieve the desired proportion of the recurrent parent genome (indicated by the dotted line). Therefore. conversion’ (Morris et al.. 1999). the in plant breeding programs (Young. 2001. if tightly-linked Although there have been numerous QTL mapping markers flanking QTLs and evenly spaced markers studies for a wide range of traits in diverse crop species. unlinked to QTLs) relatively few markers have actually been implemented of the recurrent parent are used for selection. The use of additional notype. 2003. vars in the medium to long-term (Morris et al. this would be attributable to a markers to accelerate cultivar development is some. An important study important consideration for plant breeders because the concerning the more effective integration of MAS and accelerated release of an improved variety may trans.e. However. This is an tistical methods (Doerge. Young (1999) cited two main reasons ing markers is far greater compared to conventional for this ‘cautious optimism’: improvements in mapping backcrossing (Figure 16) (Frisch et al. Therefore. 1999. In many cases. there is a ‘cautious optimism’ regarding program that simulates recombination during meiosis– the role of MAS in the future by leading researchers indicate that efficiency of recurrent parent recovery us. ... Statistical Although the initial cost of marker-assisted methodology is a vital component of mapping stud- backcrossing would be more expensive compared ies. The main introgression of QTLs and recovery of the recurrent reason for this lack of adoption is that the markers used parent may be accelerated. 2002). software using more statistically powerful methods. the time been made in the development of more powerful sta- savings could lead to economic benefits. Graph of PLABSIM (Frisch et al. low accuracy of QTL mapping studies or inadequate times referred to as ‘full MAS’ or ‘complete line validation (Sharp et al. plant breeding was the proposal of ‘advanced backcross Figure 16.. 2002). Ribaut et al. Young. despite the lack of examples of MAS be- Simulation studies using PLABSIM–a computer ing practiced. Future trends some individuals possess more of the recurrent parent genome than others. 189 smaller population sizes that are typically used in actual late into more rapid profits by the release of new culti- plant breeding programs. 2003). et al.’ holds much promise in identifying the ac- 1996. One example in barley (Han et al. Hori et al.. Summers..’ which combined QTL analysis with va.g. Skiba et al.. which enables multiple marker loci proach could be used to improve neglected or ‘orphan’ to be tested simultaneously (Ablett et al. which expressed sequence tag (EST) and microarray analysis. of high-density consensus maps greatly facilitates the tection systems. and (Gupta et al. 2003). which et al. Furthermore. comparative mapping may become more widely dance of single nucleotide polymorphisms (SNPs) and practiced (Laurie & Devos. 1998. it is anticipated that in the fu. 2003.. 2002). Ogbonnaya et al.190 QTL analysis. growing rapidly (especially from genome sequencing fect the efficiency and effectiveness of QTL mapping projects e. 2002. SNPs and data mining for new markers in the future tion of functional genomics with QTL mapping. isolate target genes by using the marker as a ‘probe’ to ture. Pflieger et al. and STSs will provide researchers with a greater ar- struction of second-generation maps. Karakousis et al. markers may by used to identify new syntenic markers pling et al. The availability development of sophisticated high-throughput SNP de. isolate homologues and conduct trans- The latest trends are to combine QTL mapping genic experiments. determined the locations of QTLs (Hayashi et al. 1995. However. 2001. 2002). Warburton et al. 2003. more ac. EST-derived mark- techniques should play an important role in the con. More impor- these methods are not too expensive.. thus elimi- which can be utilized to develop markers from genes nating the possibility of recombination between marker themselves (Gupta et al. rice). 2003. Meyer will result in a reduction in the cost of markers.. DNA sequences for the majority of genes .. the availability of more high-density maps. 1996). Wang et al. are located within the actual gene sequence. 2004. and many of these methods are mapping between related species. Comparative mapping analysis of widely-used markers are becoming faster could be used to make considerable progress in QTL and more sophisticated.. Perovic et al. commonly It is expected that the development of high- used marker techniques are constantly being simplified resolution maps will also facilitate the isolation in innovative ways (Gu et al.. with methods in functional genomics. different genetic backgrounds Ishimaru et al. cloning involves the use of tightly linked markers to tion of MAS. 1998.. described as the ‘candidate gene riety development simultaneously (Tanksley & Nelson. However. research studies and MAS (Rafalski. (Rafalski. EST and genomic sequences available in databases is We believe that several other factors will greatly af.. the number of able markers for MAS. and gene (Ellis et al. tantly. 2002. approach. 1996). To enhance the efficiency of MAS.. 2003). of actual genes (rather than markers) via ‘map- Currently. Tanksley et al. The development of more high-density (or ‘satu- New types of markers and high-throughput marker rated’) maps that incorporate SNPs.. 2004) and of an improvement in the efficiency of marker analysis wheat (Liu & Anderson. Map-based the most important factor that limits the implementa. 2003). the cost of utilizing markers is possibly based cloning’ (also ‘positional cloning’). Yamamoto & Sasaki. 2002. Koebner & 2001.. Ram.. ers.. 1995). developed for knowledge of the DNA sequence of the gene enables the study of gene expression.. gene function.. Zhang et al. and the accumulation of these se- and MAS research in the future: New developments quences will be extremely useful for the discovery of and improvements in marker technology. this ap- is multiplex PCR.. tual genes that control the desired traits (Cato et al. novel applications and technology improvements screen a genomic library (Tanksley et al. or gene analogues. Valuable lessons learnt from past research are likely 2001.. At present. 2001. 2001. 2002)... 2003.. to encourage more researchers to develop reliable These methods can also be utilized to identify SNPs markers and plant breeders to adopt MAS. and independent verification. 2001. curate phenotypic data. 2004. 2001). 2002).. Kantety et al. 2004). methods for detection and Lombard & Delourme. The use of gene sequences derived from ESTs However. These techniques include the design of ‘perfect’ or ‘diagnostic’ markers.. EST-derived and SNP markers are Young (1999) emphasized that scientists must realise usually integrated into existing maps that have already the necessity of using larger population sizes. rice automated (Ablett et al. 2001). Donini crops such as pearl millet (Gale & Devos. 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