Advanced Backcross QTL Method: A Brief Overview

20 Trends in Biosciences 10 (1), 2017 Trends in Biosciences 10(1), Print : ISSN 0974-8431, 20-25, 2017

REVIEW PAPER

Advanced Backcross QTL Method: A Brief Overview A. NISHANT BHANU*,YUGANDHAR GOKIDI AND M. N. SINGH Department of Genetics and Plant Breeding, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh *email: [email protected]

ABSTRACT Advanced backcross (AB) QTL analysis is a method which combines QTL analysis with variety development. AB-QTL approach displayed that the genetic potential of exotic germplasm cannot be predicted based on phenotype alone.This approach is an efficient method to utilize wild species by simultaneous discovery and transfer of valuable QTLs from exotic germplasm into elite breeding lines. Following this strategy, in the advanced backcross design, QTL analysis is delayed until a later generation like the BC2 or BC3 generation and negative selection is exercised to reduce the frequency of the donor parent alleles. QTLNILs can be derived from advanced backcross populations in one or two additional generations and utilized to verify QTL activity. If efficaciously employed, advanced backcross QTL analysis can prove to be a potential method to exploit unadapted and exotic germplasm for the quantitative trait improvement of a number of crop plants. Key words

Advanced backcross, QTL, NILs, exotic germplasm, negative selection

Most traits of agronomic importance, including yield, nutritional quality and stress tolerance, are quantitatively inherited (Allard 1960; Hallauer and Miranda 1988). Each of these traits is controlled by many genes. Mather (1949) termed this as polygenes. The study of the genetics of quantitative traits in different plant system is an important area of plant science research as they are a common feature of natural variation present in the population of various crop plants. In the earlier period, probably, up to 1980, the study of quantitative traits involved various statistical means such as means, variances and covariances of relatives. Such studies provided conceptual basis for partitioning the total phenotypic variance into genotypic and environmental variances. Further, the genetic variances partitioned into different componentsas additive, dominance and epistatic variances. From this information, it became feasible to estimate the mode of heritability of trait, the response of the trait to selection process and also the number of genes that controlled the trait of interest. With the advent of molecular markers in the 1980s,identification of quantitative trait loci (QTL) and mapping a trait to a specific chromosome region(s) became feasible by investigating marker–trait linkages in biparental mapping populations.Using QTL analysis, linkage maps can be exploited for detection of chromosomal regions governing traits controlled by either oligogenes or polygenes. The first step is QTL discovery where parental lines are first identified for one or more contrasting quantitative traits of agronomic importance (e.g., yield, quality). The parents are hybridized and segregating

population is created in which marker-trait linkages are identified. The second step is to utilize knowledge of QTL map locations to create asuperior variety. Wild relatives of crop plants are the source of novel genes lost during the domestication process. It has been proved time and again that despite the inferior phenotype, the exotic germplasm contain QTLs that can increase the yield and quality of elite breeding lines. However, these QTLs are often linked with undesirable traits making their application difficult. To overcome such hurdles further unlock the variation present in wild relatives, Tanksley and Nelson (1996) proposed a new molecular breeding strategy, using the advanced backcross (AB) QTL method which integrates QTL analysis with variety development to simultaneously identify and develop an interspecific population for mapping a desirable trait found in the wild/ exotic parent and transfer the trait into the cultivated parent. This review provides a precise overview on advanced backcross QTL including its application along with its advantages and limitations in crop improvement. Besides these, brief information of crops where the AB-QTL analysis has been used for the detection and introgression of QTLs/ genes has been incorporated.This compact and comprehensive review can be of assistance to related researchers.

QTL Analysis QTL analysis is specialized methodin which genetic linkage maps are constructed to locate loci (QTLs) that affect a quantitative trait and estimate the genetic effect of QTLs on the trait.QTL mapping studies have been reported in most of the crop plants for diverse traits like yield, quality, disease, insect pest resistance, abiotic stress tolerance and environmental adaptation. The theory of QTL mapping was first described by Sax (1923), where he noticed that seed size (a complex trait) in bean was associated with seed coat colour (a simple, monogenic trait). Thoday (1961) elaborated this concept and suggested that if the segregation of simply inherited monogenes could be used to detect linked QTLs, then it should eventually be possible to map and characterize all QTLs involved in complex traits. Therefore, the principle of QTL analysis is based on the principle of detecting an association between phenotype and the genotype of markers expecting that genes and markers segregate via chromosome recombination. The process of QTL mapping involves the following major steps, such as: a)

Development of appropriate mapping population [F2 or Fx derived families, backcross (BC), double haploids (DH), recombinant inbred lines (RILs) and near isogenic lines (NILs)],

b)

Precise phenotyping for related traits (morphological

BHANU et al., Advanced Backcross QTL Method: A Brief Overview

characters, agronomic traits, disease and pest scores, drought resistance, etc.) c)

Deciding the type of marker(s) and identification of polymorphism,

d)

Genotyping of the mapping populations with polymorphic markers,

e)

Construction of genetic maps using statistical programs and

f)

QTL mapping using both genotypic and phenotypic data

Need for alternative approach With the advent of the molecular era and use of markers and detection of QTLs, there have been numerous reports on the use of molecularmarker-based methods to detect, map and characterizethe loci responsible for quantitative traits in crops.There are examples where molecular marker techniques have led to the creation of new crop varieties enhanced for one or more quantitative traits. Despite the successes in the recent past, QTL discovery and variety development are still a separate processes.This not only increases the time required for new variety development, but also reduces the probability of successfully using QTL information to produce a superior crop variety. In addition, most breeding-related QTL studies are targeted toward manipulating quantitative trait variation already existing within elite germplasm. Thus, to obtain a major outcome of QTL analysis in genetic improvement of crop plants it is required that QTL discovery and variety development must be integrated into a single process. Furthermore, beneficial alleles must be identified and introduced in elite germplasm using QTL analysis consequently broadening the genetic base of the crop species and enhancing the rate of genetic improvement. Thousands of accessions are present for most of the major crop plants. Among these, in reality only a few accessions have contributed to the development of new elite varieties. Hence, there is a need to exploit the genetic potentiality of the majority of the unadapted and wild germplasm.However, there are problems associated with using unadapted/wild germplasmto improve quantitative traits. i.

Linkage drag:Genetic diversity of crop plants is the foundation for the sustainable development of new varieties. Sufficient genetic diversity exists in the form of landraces and wild relatives. They are the reservoirof many genes which can be the basis challenges which arises due to the various biotic and abiotic stressesand canbe incorporated via hybridization/ backcross breeding scheme to enhance the genetic base.However, the crop improvement utilizing wild relatives have often been fraught with linkage drag associated them. To reduce the problems associated with linkage drag molecular linkage maps plays a role by allowing selection for individuals containing recombinant chromosomes which break linkage drag. Tanksley et al., 1989 estimated and reported that theuse of molecular maps can reduce linkage drag at leasttenfold in comparisonto the time needed for traditional breeding.

ii.

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Inferior phenotypes of most of the unadapted germplasm:With respect tophenotype of elite varieties/germplasm,unadapted germplasm is almost always inferior.Frey et al. (1981) edified that despite their inferior phenotypes, wild accessions contain several genes that are useful to improve the quantitative traits.

QTLs have been identified and transferred from an unadapted or wild species into elite cultivated varieties using molecular markers. F2, BC1 or RIL populations have been efficiently utilized for QTL mapping. However, significant drawback has been found associated with the detection and transfer of QTLs from the wild germplasm to the elite germplasm.

Shortcomings of the balanced populations: i.

Occurrence of undesirable QTL alleles of wild germplasm in high frequency leading to reduction or elimination of the ability to collect significant data on yield and yield attributing traits.

ii.

For a breeding program it is desirable to identify QTLs with less or no epistatic interactions. As the donor alleles are higher in the balanced population, more difficulty is experienced in discerning the epistatic interactions.

iii.

Due to the large genetic and phenotypic variance created by the segregation of donor alleles in highfrequency subtle or negative pleiotropic effects may go undiscovered.

The donor segment is not small enough to evaluate the effect of QTL in the mapping populations. Paterson et al., 1990 informed that an advanced mapping population in which small chromosomal regions have segregated in a highly homogeneous background manifests a propitious substitute to locate such QTLs. Consequently, the above mentioned problems can possibly be solved by delaying the QTL analysis for an advanced generation (e.g., BC2, BC3, etc).

Advanced Backcross QTL Advanced backcross (AB) QTL analysis (Tanksley and Nelson 1996), integrates QTL analysis with variety development, by identifying and transferring the valuable QTL alleles from unadapted to cultivated germplasm in a single process. In this approach, QTL and marker analyses are performed in advanced generations, like BC2 or BC3. The power of detection of different types of QTL differs in selfing populations and backcross populations. Backcross populations are less powerful in detecting a donor QTL having some degree of recessive gene action. Nevertheless, the power of detection in backcross population increases with the degree of dominance. The completely dominant or over-dominant QTLs can be detected with efficiency equivalent to or greater than that of selfing populations. Backcross population does not prove to be efficient in detecting QTLsrequiring epistatic interactions.However, they are more competent and usefulthan selfing populations in detecting the recessive and epistatic QTLs as these QTLs contribute very slightly to the phenotypic variance of background populations.

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Trends in Biosciences 10 (1), 2017

Consequently, detection of additive, dominant and overdominant QTLs is boosted in backcross generations in comparison to selfing generations where recessive orepistatic QTLs are segregating simultaneously in the population (Tanksley and Nelson, 1996). The objective of QTL analysis is to detect the valuable QTL alleles from a donor genome and subsequently their transfer into elite breeding lines. In this context, one must have the idea concerning number of additional generations of backcrossing required and number of individuals needed to be sampled, to attain the lines having segment of the donor chromosome with the valuable QTL in the background of recurrent parent genome. Those lines are referred as QTL/nearly isogenic lines or QTL-NILs (Tanksley and Nelson, 1996). Tanksley and Nelson, 1996 propounded two factors that are important in determining this, which are (1) maximum size (in centimorgans) of the donor segment designating the QTL and (2) the amount of residual donor genome (unlinked to the targeted QTL) still present in the genome. In this context, the backcross populations get skewed toward recurrent parent alleles which make them superior over selfing generations. QTL-NILs can be derived from BC1or BC 2 derived populations, but for this screening of large number of individuals i.e. around 5,000 or 10,000 is required respectively. However, selection can be exerted to eliminate non-targeted donor segments by screening a smaller number of individuals over two sequential generations (e.g., a backcross followed by a selfing). Thus, in contrast to the BC1 and BC2, QTL-NILs can be derived directly from BC3BC 5 selections from a comparatively small number of individuals. In the other words, we can say that the more advanced the backcross population, the simpler it will be to derive a desired QTL-NILs. Based on the above considerations, “Advanced Backcross QTL Analysis” can be applied effectively to detect and interogress QTLs simultaneously in which QTL mapping is delayed to either BC2 or BC3 generations. Use of statistical tools will assist in detection of additive, dominant and over-dominant QTLs in the advanced backcross generations. Selection can be implementedto recognize and isolate individual plants that are sufficiently similar to the recurrent parent for advancing to extract QTL-NILs which may serve as a parent in breeding program or directly as improved varieties. They can also be used to further confirm and fine map selected QTLs. The potential applications and limitations of AB-QTL analysis with respect to crop improvement through plant breeding are discussed below.

Application of AB-QTL analysis in crop improvement The utility of the AB-QTL approach has been tested in numerous crops species and proved to be a feasible method in crop breeding (Grandillo and Tanksley, 2005).

AB-QTL in self pollinated crops Single elite inbred variety is initially crossed to an unrelated donor line to generate BC1 progeny (around 100 plants). Plants with desirable characters are selected from the BC 1 progeny and this selected BC1 are crossed again

with the recurrent parent to produce the BC2 progeny of around 200 individuals.Then the BC2/BC3 generation plants are evaluated in replicated trials and genotyped for marker trait loci and selfed to produce BC2S1/BC2S2 progeny. The genotype and phenotype data are subjected to QTL analysis to identify donor genome regions containing favourable QTL alleles.BC2S1 or BC2S2 families assist in detection of some recessive QTL donor alleles in additionto the expected dominant and additive donor QTLalleles. Ultimately QTLNILs are extracted from the superior BC2S1/BC2S2 which is used to confirm the findings from the QTL mapping or to fine map the detected QTLs. The outperforming QTL-NILs can be usedas parent in future breeding program or as new varieties (Tanksley and Nelson 1996; Singh and Singh 2015).

AB-QTL in cross pollinated crops Advanced backcross QTL analysis could be applied to cross pollinated crops through a slight modification in the strategypresented above. In case of the cross pollinated crops the elite inbred parent e.g. inbred A is used as the recurrent parent which is being involved in the production of commercial hybrid derived from the single cross A x B. Hybridization and backcrossing of donor with the recurrent parent is performed to produce the BC 2 population. The selected plants from the BC2/BC3 are genotyped for marker loci. Instead of selfing the BC2/BC 3 are crossed with the inbred B to produce BC2F1 families and later the phenotyping is performed for this. The marker and the phenotypic data are used for the QTL analysis. On the basis of the QTL analysis of this data, favourable QTLs from the donor parent are identified, eventually the QTL-NILs could be generated. Using this technique, QTL analysis have been conducted in crops like Tomato, Wheat, Barley, Rice and Cotton. Some examples of AB-QTL analysis conducted in crop genetics and breeding have been listed in table 1.

Advantages and limitations of AB-QTL Approach The potential applications and limitations of AB-QTL analysis with respect to plant breeding are discussed below.

Advantages Since the smaller number of genes from donor parent will be present in BC2 or BC3, the undesirable effect of wild species on the elite germplasm is reduced and the effect of individual QTLs is measured more precisely. As the phenotypic selection is delayed for advanced generation, the frequency of deleterious or undesirable alleles from the donor is further reduced. Therefore, the problems with deleterious effects which are associated experienced with balanced population (F2, BC1, or RILs) are minimized in this method. In addition, to have a better prediction of the effect of QTL, epistatic effect should be minimized. MAS performed in advanced generation is more effective than in F2 or BC1 asaccumulation of the donor alleles is minimised in advanced generation due to breaking of assembly of favourable epistatic gene combination through recombination. Due to this, AB population is skewed more towards the recurrent parent genome and the epistatic interaction between the favourable epistatic interactions between the recurrent parent and tester alleles are comparatively less distorted. In addition, QTL-NILs (lines which differ from its parent in only one genomic location,

BHANU et al., Advanced Backcross QTL Method: A Brief Overview

Table 1.

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Some examples of AB-QTL analysis in conducted in cropplants.

Crop

Wild/Donor

Trait Studied

Reference

Wheat

Synthetic wheat line (W-7984)

Yield and yield component traits

Huang et al. (2003)

Synthetic wheat line (XX86)

Agronomic traits

Huang et al. (2004)

Synthetic wheat line (TA 4152-4)


Narasimhamoorthy et al. (2006)

Synthetic hexaploid wheat accessions (Syn022) and (Syn086)

Baking quality traits

Kunert et al. (2007)

Synthetic wheat accession (Syn022L)

Leaf rust resistance

Naz et al. (2008)

Synthetic hexaploid wheat accession (Syn084)

Drought tolerance

Ibrahim et al. (2010)

O. rufipogon (IRGC 105491)

Agronomic traits

Xiao et al. (1998)

Rice

Barley

Tomato


Yield

Xiao et al. (1996)


Yield, yield component and morphological traits

Thomson et al. (2003)


Agronomic traits

Septiningsih et al. (2003a)


Seed quality traits

Septiningsih et al. (2003b)

O. rufipogon

Yield, yield component Traits

Marri et al. (2005)



Xie et al. (2008)



Cheema et al. (2008)

O. sativa spp.Japonica (Koshihikari)

Grain shape

Nagata et al. (2015)

H. vulgare ssp. spontaneum


Pillen et al. (2003)

H. vulgare ssp. spontaneum (ISR42-8)

Powdery mildew, leaf rust and Scald

Von Korff et al. (2005)


Agronomic traits

von Korff et al. (2006)


Malting quality traits

Von Korff et al. (2008)


Resistance to powdery mildew and leaf rust

Schmalenbach et al. (2008)


7 agronomic traits

Schmalenbach et al. (2009)

L. pimpinellifolium (LA1589)

Horticulture traits

Tanksley et al. (1996)

L. peruvianum (LA1706)

Fruit weight

Fulton et al. (1997)

L. hirsutum (LA1777)

Agronomic traits

Bernacchi et al. (1998)

L. parvifl orum

Horticultural traits

Fulton et al. (2000)

S. harbochaites

Ascorbic acid

Stevens et al. (2007)

Pepper

C. frutescens

Yield related traits

Rao et al. (2003)

Maize

RD3013(Iodent)

Grain yield, grain moisture and plant height

Ho et al. (2002)

Dan232 (dent type maize)

Grain yield components

Li et al. (2007)

Cotton

Dan232 (dent type maize)

9 plant traits

Li et al. (2008)

Z. nicaraguensis

Root aerenchyma formation

Mano and Omori (2008)

G.barbadense (Pima S6)

Fiber elongation

Chee et al. (2005a)


Fiber length

Chee et al. (2005b)


Fiber fineness and micronaire

Draye et al. (2005)

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Trends in Biosciences 10 (1), 2017

ideally a single favourable QTL) can be created by one or two additional backcrossing with selected QTL. Also, the opportunity for useful meiotic recombination occurs as the generation is advanced, the deleterious effect due to linkage drag is also minimized in the advanced generations. In ABQTL, the mean performance of the advanced backcross families is skewed towards the elite parent that provides opportunity to detect the subtle pleiotropic effect of introgressed QTLs (Tanksley and Nelson, 1996).

Limitations

Allard, R.W. 1960. Principle of plant breeding. John Wiley and Sons Co. New York. p. 485. Bernacchi, D., Beck-Bunn, T., Eshed, Y., Lopez, J., Petiard, V., Uhlig, J., Zamir, D. and Tanksley, S. 1998. Advanced backcross QTL analysis in tomato. I. Identification of QTLs for traits of agronomic importance from Lycopersicon hirsutum. Theoretical and Applied Genetics,97: 381–397. Chaïb, J., Lecomte, L., Buret, M. and Causse, M. 2006. Stability over genetic backgrounds, generations and years of quantitative trait locus (QTLs) for organoleptic quality in tomato. Theoretical and Applied Genetics, 112: 934–944.

Despite of having so many advantages of this method, there are still some cases where the effortless application of this method is limited. Advanced backcross QTL analysis is not likely to be useful in the crops with relatively longer generation time (> 2 years). Use of this method in longgeneration perennial crops are limited because intricacy in development and exploitation of the necessary population and QTL-NILs. As the success of this method in production of any commercial or hybrid varieties depends on the availability of the inbreds, this method is strenuous to apply in the crops for which inbred lines do not exist. In addition, this method is also difficult to apply inhighly heterozygous, outcrossing crops like alfalfa or clonally propagated crops like potato for which inbred lines are not commonly employed in breeding programs.

Chee, P., Draye, X., Jiang, C. X., Decanini, L., Delmonte, T. A., Bredhauer, R., Smith, C.W. and Paterson, A.H. 2005a. Molecular dissection of interspecific variation between Gossypium hirsutum and Gossypium barbadense (cotton) by a backcross-self approach: I. Fiber elongation. Theoretical and Applied Genetics,111: 757–763.

CONCLUSION

Draye, X., Chee, P., Jiang, C. X., Decanini, L., Delmonte, T.A., Bredhauer, R., Smith, C.W. and Paterson, A.H. 2005. Molecular dissection of interspecific variation between Gossypium hirsutum and G. barbadense (cotton) by a backcross-self approach: II. Fiber fineness. Theoretical and Applied Genetics, 111: 764– 771.

The advent of molecular maps and the resulting quantitative trait locus (QTL) mapping technology has provided strong evidence that despite the inferior phenotype, exotic germplasm is likely to contain QTLs that can upsurge the yield and quality of elite breeding lines. Numerous QTL-mapping studies have been reported for many crops in previous years, however, their contribution to breeding new varieties has been limited. AB-QTL strategy which advocates the delay of QTL analysis till BC 2 or BC3has represented a very effective way to exploit valuable wild alleles and transfer them into elite cultivars to improve their performance. In the last 20 years, AB-QTL populations has been utilizedin most of the major crop speciescollectively revealing that this approach hassubstantialpotential in unlocking favourable alleles from the wild species parents.This method not only results in improving elite varieties, but it also provides an effective strategy for selectively broadening the genetic base of crop species, especially those with a narrow germplasm base. By means of the AB-QTL method NILs can quickly be developed once a favourable QTL has been identified by one additional backcrossing to the recurrent parent. Finally, these QTL-NILs are the powerful resource for the genetic dissection of QTLs as in this case the target QTL is the major genetic source of variation due to the absence of other segregating QTLs. This further provides the opportunity for eventual map-based cloning of the underlying gene, which has now been accomplished in a many major crop species.

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Received on 15-12-2016

Accepted on 20-12-2016