Peruvian Journal of Agronomy 4(3): 104–120 (2020) ISSN: 2616-4477 (Versión electrónica) DOI: http://dx.doi.org/10.21704/pja.v4i3.1490 http://revistas.lamolina.edu.pe/index.php/jpagronomy/index © The authors. Published by Universidad Nacional Agraria La Molina Received for publication: 19 August 2020 Accepted for publication: 20 November 2020 Marker-assisted selection:A smart biotechnological strategy for modern plant breeding Selección asistida por marcadores: Una estrategia biotecnológica inteligente para el fitomejoramiento moderno Shruti Shrestha1*; Sudeep Subedi2; Jiban Shrestha2 *Corresponding author: shrutis2903@gmail.com https://orcid.org/0000-0002-8954-5538 Abstract Plant breeders and geneticists use molecular marker-assisted selection also called as MAS as a useful approach for breeding of plant to make selection more efficient and speed up the breeding cycle. MAS can be more efficient, effective, and reliable than phenotypic selection. Molecular markers are useful to identify the economically important traits in the breeding population for further manipulation in a short time. Due to the applicability of markers at the seedling stage ensuring high precision at the reduced level of cost, marker-assisted selection offer the chances to improve responses from selection. The MAS using DNA level polymorphism accelerate the pace of selection. The main marker technologies applied are chiefly co-dominant markers i.e. microsatellite markers/SSR (Simple Sequence Repeats) marker, RFLP (Restriction Fragment Length Polymorphism) marker and SNPs (Single nucleotide polymorphisms). This review overviews the various MAS technologies and their applications in crop improvement programs. Keywords: Breeding, Marker Assisted Selection (MAS), Single nucleotide polymorphisms (SNPs) Resumen Los fitomejoradores y genetistas utilizan la selección asistida por marcadores moleculares, también denominada MAS (por sus siglas en inglés), como un enfoque útil para la reproducción de plantas para hacer la selección más eficiente y acelerar el ciclo de reproducción. MAS puede ser más eficiente, eficaz y confiable que la selección fenotípica. Los marcadores moleculares son útiles para identificar los rasgos económicamente importantes en la población reproductora para su posterior manipulación en poco tiempo. Debido a la aplicabilidad de los marcadores en la etapa de plántula, lo que garantiza una alta precisión a un nivel de costo reducido, la selección asistida por marcadores ofrece la oportunidad de mejorar las respuestas de la selección. El MAS que usa polimorfismo a nivel de ADN acelera el ritmo de selección. Las principales tecnologías de marcadores aplicadas son principalmente marcadores codominantes, es decir, marcadores de microsatélites / marcador SSR (repeticiones de secuencia simple), marcador RFLP (polimorfismo de longitud de fragmentos de restricción) y SNP (polimorfismos de un solo nucleótido). Esta revisión describe las diversas tecnologías MAS y sus aplicaciones en programas de mejora de cultivos. Palabras clave: Reproducción, selección asistida por marcadores, polimorfismos de nucleótido único (SNP) 1 Agriculture and Forestry University, Rampur, Chitwan, Nepal 2 Nepal Agricultural Research Council, National Plant Breeding and Genetics Research Centre, Khumaltar, Lalitpur, Nepal Cite this review: Shrestha, S., Subedi, S., & Shrestha, J. (2020). Marker-assisted selection: A smart biotechnological strategy for modern plant breeding. Peruvian Journal of Agronomy, 4(3), 104–120. http://dx.doi.org/10.21704/pja.v4i3.1490 Introduction to MAS Agricultural researches are being carried out with the primary aim of improving different crop species keeping in mind the desirable traits. Although there are several revolution and more sophisticated process, there is the need of introducing new molecular technology in our breeding scheme like Marker Assisted Selection which is more efficient than conventional breeding schemes (Lema, 2018). Detectable differences are seen due to the presence of markers’ specific biomolecules which contain proteins among various species. A molecular marker, used based on naturally occurring DNA polymorphism is a sequence of DNA that can be identified easily. The ideal marker S. Shrestha; S. Subedi; J. Shrestha Peruvian Journal of Agronomy 4(3): 104–120 (2020) 105 must be easily reproducible, polymorphic, easy, readily and cheaply detected and must have even distribution throughout the genome (Nadeem et al., 2018). Molecular marker is a powerful tool found in Quantitative trait loci (QTL) that helps in detection of the genes carrying desirable traits. It consists of a specific molecule that helps to identify different species. A short DNA sequence, like a sequence that surrounds a single base-pair change (single nucleotide polymorphism, SNP), or like mini and microsatellites which are long one (Al- Samarai & Al-Kazaz, 2015). Within genome there exist many regions that contain genes that are associated with a quantitative trait like yield, height, and is known as quantitative trait loci (QTLs). The progress of DNA markers in the 1980s resulted in the selection of QTLs that helps in the representation of quantitative traits (Collard et al., 2005). In agriculture, for the formation of linkage map DNA markers are mainly used for diverse crop species and this linkage map is utilized for determining chromosomal regions that contain genes that control simple traits and quantitative traits using QTL 170 analysis (Mohan et al., 1997). Linkage maps construction and undergoing QTL analysis which helps in defining particular genomic regions that is associated with particular traits is known as QTL /genetic/gene/genome mapping (McCough & Doerge, 1995; Mohan et al., 1997). The process of selecting genes using such markers is referred to as marker-assisted selection (MAS) and is relatively a new discipline of molecular breeding. There are various types of markers available and the use of particular marker depends upon its availability, objectives of the project, required quantity and quality of DNA, level of polymorphism detecting efficiency, the required time for conducting analysis, cost per unit information, genetic diversity of species under consideration and their utility across the population. Like, for self-pollinated, RAPD (Random-amplified polymorphic DNA) markers are more useful than RFLPs for polymorphism detection within a gene pool. For characterizing other species, RFLPs that is mapped in one population can be used as heterozygous probes. Markers have been elaborated and used for enhancing global food production monitoring its economically important traits. The use of molecular markers has led to the improvement of important crop like rice (Mackill et al., 1999). It has been used for example, in the enhancement of heterosis for the grain yield in the B73xMo17 Elite Single Cross hybrid Maize and also we can find successful example of MABC (Marker Assisted Back Crossing) and Forward crossing in maize (Abler et al., 1991). Even in wheat, Multiparent advanced generation intercross (MAGIC) approach is being used in UK and Australia to develop multi-parent recombinant inbred lines (RILs). For whole genome profiling as well as for background screening, Single nucleotide polymorphisms (SNPs), and diversity array technology (DArT) have also been used widely (Gupta et al., 2010). The improvement has also been made using barley (Thomas, 2003), oilseed (Snowdon & Friedt, 2004), horticultural crops (Mehlenbacher, 1995), and pulses (Kelly et al., 2003). RFLP markers for the cereal cyst nematode have been used in the selection of Cre1 resistance gene in wheat (Ogbonnaya et al., 2001). This review will give important information and a clear concept about the newly emerging biotechnological interventions using markers. The rice crop is used as an example to show recent advances in MAS. Characteristics of markers in MAS Co-dominant markers provide more information than dominant markers as there will be no masking action. So, markers should be co-dominant in MAS approaches. Marker loci should be extensively and evenly distributed so that it can show all resistant genes present of the concerned traits in the chromosome. The detection work of markers should be rapid, easy, and simple and this detection system should be cost-effective and amenable to automation. Markers should be highly reproducible in all cells. The marker system should be highly polymorphic to show differences between genotypes that contain and that do not the target gene. The marker should be reliable in nature which map close to the target gene. Closer the marker to the target gene, lower will be the recombination frequency. Also, rather than using a marker if two markers are used flanking the target gene, there will be higher accuracy of Marker Assisted Selection. Types of markers techniques Different kinds of DNA markers have been used based on different polymorphism detecting techniques (southern blotting, northern blotting, PCR – polymerase chain reaction, and DNA sequencing) (Collard et al., 2005). The different molecular marker techniques are given in Table 1. Procedure of MAS The general procedure of MAS is given in Figure 1 (Rana et al., 2019). Marker-assisted selection involves the following major methods: (1) screening of populations (e.g., F2, F3, recombinant inbred lines, double haploids, etc.) for genotypes of interest based on molecular markers, (2) marker-assisted backcross, where one or more genes per QTLs of interest are transferred from a donor parent to a recipient parent by repeated backcrossing to improve the target trait, (3) gene pyramiding schemes, where genes (two or more) identified in multiple lines/parents are accumulated into a single genotype, (4) marker-based recurrent selection, a complex scheme used for more loci involving several generations of selection and random mating of selected individuals, (5) selection based on an Marker-assisted selection: a smart biotechnological strategy for modern plant breeding. September - December 2020 106 SN Techniques References 1 AFLP (Amplified fragment length polymorphism) used for DNA fingerprinting (Vuylsteke et al., 2007) 2 AP-PCR (Arbitrarily primed PCR) used for genomic fingerprinting (Welsh & McClelland, 1991) 3 AS-PCR (Allele-specific PCR) used for detection of mutations, polymorphisms, and haplotypes (Bottema et al., 1993) 4 ASAP (Allele-specific Associated Primers) used for developing resistance in Pisum sativum against bean yellow mosaic virus (Yu et al., 1996) 5 CAPS (Cleaved amplified polymorphic sequences) used for preparation of genetic map (Shavrukov, 2016) 6 DAF (DNA amplification fingerprinting) used for producing a characteristic spectrum of short DNA products useful for detecting genetic differences (Caetano-Anollés et al., 1991) 7 ISA (Inter-SSR amplification) used for genome fingerprinting (Zietkiewicz et al., 1994) 8 RAPD (Random-amplified polymorphic DNA) used for comparing DNA sequences (Kumar & Gurusubramanian, 2011) 9 RFLP (Restriction fragment length polymorphism) used to characterize the microbial communities (Schütte et al., 2008) 10 SAP (Specific amplicon polymorphism) for analysis of PCR products amplified from mapped loci of rice genomic DNA (Williams et al., 1991) 11 SCAR (Sequence characterized amplified region) used for Bdv2 gene’s molecular confirmation in wheat germplasm and assessment for resistance against barely yellow dwarf viruses (Kausar et al., 2015) 12 SPAR (Single Primer Amplification Reactions) for the assessment of diversity in Jatropha curcas L. (Ranade et al., 2008) 13 SSLP (Microsatellite simple sequence length polymorphism) for its characterization in rice (Panaud et al., 1996) 14 SSR (Simple sequence repeats) for analysis of its polymorphism between N22 and Uma rice varieties (Waghmare et al., 2018) 15 STS (Sequence tagged sites) for its Generation and validation from diverse genotypes of dioecious Jojoba (Heikrujam et al., 2014) Table 1 Different Molecular Marker Techniques Marker-assisted selection Figure 1. Basic procedure for marker-assisted selection (Rana et al., 2019) S. Shrestha; S. Subedi; J. Shrestha Peruvian Journal of Agronomy 4(3): 104–120 (2020) 107 index combining molecular and phenotypic data, and (6) genomic selection, in which genomic estimated breeding value is obtained using information from genome-wide markers. MAS in gene pyramiding Gene pyramiding refers to the incorporation of a desirable or resistant gene which has known effects on the target trait from multiple parents to develop superior cultivars. The more resistant gene present, the more challenging it becomes to break the resistance of the plant. Like if one plant has only one resistant gene then it may only survive for 1-2 years but with the application of gene pyramiding it may survive for many years because pathogen requires double or multiple mutation to break resistant in cultivars. Three bacterial resistance genes (xa5, xa13, and Xa21) were introgressed in a rice cultivar Samba Masuri which proved to have durable resistance in rice with no yield penalty (Kottapalli et al., 2010). Pyramiding is very precise as it includes one gene only at one time. Some important things that are to be considered while selecting such genes are the pathogens should be avirulent to the resistant gene i.e. allele frequency of corresponding Avr gene must be 1 and this is how cultivar remains durable (Joshi & Nayak, 2010). Cultivar with durable and broad spectrum resistance is desired and can be achieved by combing different resistance genes through marker assisted gene pyramiding (Liu et al., 2000). The main advantages of using it are it helps to develop durable resistance, eliminates extensive phenotyping, control linkage drag and breeding duration are reduced. Some examples of application of MAS for gene pyramiding in various crops are presented in Table 2. When the markers are tightly linked to resistant gene, with the help of marker phenotype numbers of the resistant gene carried by progeny can be identified indirectly. It has been found that through the incorporation of multiple genes, durable (broad spectrum) resistance against certain pathogens can be obtained (Kloppers & Pretorius, 1997; Shanti et al., 2001). When qualitative resistance fails, quantitative resistance can assist as an insurance policy as in the single stripe rust gene and two QTLs pyramiding (Castro et al., 2003). We can undergo pyramiding using multiple parents and their number of genes as pyramiding into indica rice cultivar PR106 with the use of three bacterial blight resistance genes (Singh et al., 2001). Pyramiding of genes like Xa1, xa5, xa13, Xa21, Xa26 and Xa27 in rice (Oryza sativa L.) for resistance to bacterial leaf blight disease has also been reported (Chu et al., 2006; Chukwu et al., 2019; Sun et al., 2004). Marker Assisted Gene Pyramiding has also been done for bacterial blight and blast resistance with the use of marker-assisted backcrossing strategy and pyramiding two Bacterial Blight resistance genes (Xa21 and xa13) and two major blast resistance genes (Pi54 and Pi1) into mega rice variety “Tellahamsa” (Jamaloddin et al., 2020). MAS in back crossing Molecular markers are broadly used in improving efficiency of backcrossing to develop high yielding superior cultivars that contributes to the higher yield. In this backcrossing process, the donor’s genetic background is removed and that of a recurrent parent is recovered. This process takes longer time and is unreliable and therefore MAS in back crossing aids in transferring the beneficial gene to the recurrent parent determining young plants containing preferred trait and removing all the stray donor genes. Effectiveness of marker-assisted backcrossing depends on each backcross generation population, a distance between the target locus and marker, and the numbers of background markers in use (Hasan et al., 2015). Effective marker backcrossing occurs in three ways (Collard & Mackill, 2008; Holland, 2004). Firstly, Foreground selection which refers to the using of markers that control the gene of interest for its selection used for such qualities having tough or long phenotypic screening procedures, for knowing about the plants’ reproductive performance in the early stage of its growth and also for selecting recessive alleles. Secondly, a recombinant selection signifies the selection of progeny from backcross containing the gene of interest and linked flanking markers which help in reducing the undesirable gene containing in the chromosome segment of the donor and thus helps in minimizing linkage drag. Thirdly, background selection denotes the selection of the progeny from backcross that contains recurrent parent’s genome that is not linked to the target locus. This helps to recover recurrent parent with less backcrossing (even maybe in BC2) with an additional gene which is called complete line conversion. As a combination of methods, Marker assisted backcross-based gene pyramiding can be accomplished in three schemes (Servin et al., 2004) and (Malav & Chandrawat, 2016). Different Schemes of gene pyramiding are given in Figure 2. In the first scheme, F1 hybrid is produced from the cross between recurrent parent and donor parent which then gives improved recurrent parent when F1 hybrid is backcrossed up to third generation. Then, with the crossing between improved recurrent parent and other donor parent yields pyramid multiple genes. However, this is less acknowledged because it is time-consuming. In the second scheme, F1 hybrid is produced with the crossing between the recurrent parent and donor parents. Then, improved F1 is produced through intercrossing which then gives improved recurrent parent when backcrossing of improved F1 is done with the recurrent parent that may results in the loss of pyramided gene. The third scheme is the combination of the first and second scheme in which instantaneous crossing between the recurrent parent and number of donor parents takes place and the result from this cross is allowed to backcross up to the third generation and finally yields pyramided lines when intercrossed Marker-assisted selection: a smart biotechnological strategy for modern plant breeding. September - December 2020 108 Applications of MAS in rice breeding MAS in rice breeding for bacterial leaf blight Bacterial blight (BB) is one of the most destructive rice. Twenty-eight genes conferring resistance to bacterial leaf blight (BB) have been reported in rice (Nino-liu et al., 2006). Several genes have been associated with tightly linked DNA markers, and some of them have been cloned (Xa1, xa5, xa13, Xa21, Xa26, Xa27) and used for breeding BB-resistant rice cultivars. With the exception of xa5 and xa13, the BB resistance genes are dominant in nature and the markers are developed from the sequencing information of these genes, which are widely used in MAS (Chu et al., 2006). The resistance genes xa5, xa13, and Xa21 have been pyramided into an indica rice cultivar (PR106) using MAS that expressed strong resistance to BB races of India (Singh et al., 2001). MAS in rice breeding for blast disease Blast disease is one of the most serious diseases of rice. Blast resistance is governed by a specific interaction of a particular resistance (R) gene in rice with a particular avirulence gene in the pathogen. Since the initial definition of the plant resistance (R) genes by Flor (1942), many R genes have been identified. The vast majority of the known R genes is composed of proteins carrying nucleotide- binding sites and leucine-rich repeat motifs (NBS-LRR) (Jones & Dangl, 2006). Many R genes have been identified in rice and most code for NBS-LRR genes. About 40 major blast genes have been identified, about 30 genes have been mapped on different rice chromosomes, and tightly linked DNA markers have been developed. The DNA markers have been used effectively to identify resistance genes, and MAS has been applied for integrating different resistance genes into rice cultivars lacking the desired traits. The PCR-based allele-specific and InDel marker sets are available for nine blast resistance genes, and they provide an efficient marker system for MAS for blast resistance breeding (Hayashi et al., 2006). The breeding works in rice using MAS is given in Table 2. Application of MAS in other various crops The efforts and mechanism of MAS in plant breeding in various crops are given in Table 3. MAS vs Conventional breeding Conventional breeding is the traditional types of breeding which involve the production of cultivars using old tools and techniques and not as sophisticated as modern breeding technology. Marker-assisted selection makes phenotypic evaluation in laboratory relatively easy than conventional breeding. It is very hard to achieve pyramiding with the conventional methods (Collard & Mackill, 2008). The difference between MAS and conventional breeding is given in Table 4. Figure 2: Different Schemes of gene pyramiding. RP= Recurrent parent; DP= Donor parent; BC= Backcross; IRP= Improved recurrent parent. A. Stepwise transfer; B. Simultaneous transfer; C. Simultaneous and stepwise transfer. (Adopted from Malav & Chandrawat, 2016). S. Shrestha; S. Subedi; J. Shrestha Peruvian Journal of Agronomy 4(3): 104–120 (2020) 109 Crop Target trait(s) (Target gene) and Marker type Reference (a) Marker-assisted gene pyramiding Rice Bacterial leaf blight resistance (Xa1, xa5, xa13, Xa21, Xa26 and Xa27); PCR (Chu et al., 2006; Chukwu et al., 2019; Sun et al., 2004) Two Bacterial Blight resistance genes and two Blast resistance genes into mega rice variety “Tellahamsa” (Xa21, xa13 and Pi54, Pi1); pTA248 (Xa21), xa13prom (xa13), Pi54MAS (Pi54) and RM224 (Pi1) (Jamaloddin et al., 2020) Bacterial blight and Blast resistance into Indian rice variety MTU1010 (Xa21, xa13 and Pi54); SSR (Arunakumari et al., 2016) Bacterial leaf blight resistance (Xa21 and xa13); (Xa7 and Xa14); R gene pyramid of (Xa4, xa5 and Xa21) (Arshad et al., 2016) Blast resistance (Pi1+Piz-5+Pita); RFLP, PCR- based SAP (Pi-tq5, Pi-tq1, Pi-tq6, Pi-lm2); RFLP (Hittalmani et al., 2000; Tabien et al., 2000) Brown plant hopper resistance (Bph14 and Bph15); SSR and InDel markers (Hu et al., 2012) Gall midge resistance and bacterial blight to RPHR-1005 (Gm4, Gm8 and Xa21); SSR (Kumar et al., 2017) Blast resistance and bacterial blight resistance in GZ63S (Pi9 and Xa23); SCAR Blast resistance genes in Swarna-Sub1 (Pi1, Pi2, and Pi54) (Patroti et al., 2019) Stripe Disease Resistance and Eating Quality of Wuyujing 3 (Stv-bi and Wx-mq) ; PCR (Tao et al., 2016) (b) Marker assisted backcrossing Rice High-yielding drought-tolerant NILs of Sabitri 2 QTLs (qDTY3.2 and qDTY12.1) (Dixit et al., 2017) Bacterial blight resistance (xa5, xa13, and Xa21); SSR (Ramalingam et al., 2017) Resistance to blast, gall Midge, submergence, and salinity in a released rice variety CRMAS2621-7-1 blast (Pi2, Pi9), gall Midge (Gm1, Gm4), submergence (Sub1), and salinity (Saltol); SSR (Das & Rao, 2015) Bacterial blight resistance (Xa23) (Ji et al., 2014) Bacterial blight resistance in deepwater rice variety, Jalmagna (xa5 + xa13 + Xa21); STS (Pradhan et al., 2015) Brown plant hopper resistance (Bph14 and Bph15); SSR and STS (Xu, 2013) Bacterial blight resistance in Improved Samba Mahsuri (Xa38); SSR (Yugander et al., 2018) Blast resistance (Pi54, Pi1 and Pita); SSR and STS (Khan et al., 2018) Bacterial blight and blast resistance gene into JGL1798 (Xa21,xa13 and Pi54); SSR (Swathi et al., 2019) Blast resistance in variety ADT43 (Pi1, Pi2 and Pi33); SSR (Divya et al., 2014) Cooking and eating quality (Waxy gene region); AFLPs (Zhou et al., 2003) Bacterial blight and blast resistance into RPHR-1005 (Xa21 and Pi54); SSR (Kumar et al., 2016) (c) Marker-assisted validation Rice Bacterial blight resistance (Xa39); SSR (Zhang et al., 2015) Bacterial blight resistance (Xa40); RM27320 and ID55 (Kim et al., 2015) Heat resistance (qHTSF4.1); M4 (Nogoy et al., 2016; Ye et al., 2015) Deep roots (QTLs on 1, 2, 7 and 9 chromosomes); RFLP and SSR (Hasan et al., 2015) Heading date (QTLs Hd1,Hd4, Hd5, or Hd6); RFLP, STS, SSR, CAPS, dCAPs (Hasan et al., 2015) Quality (Waxy); RFLP (Hasan et al., 2015) Brown plant hopper (Bph25, Bph26) RM6273, RM6775 (Kurokawa et al., 2016) Table 2. Breeding works in rice using MAS Marker-assisted selection: a smart biotechnological strategy for modern plant breeding. September - December 2020 110 Crop Target trait(s) (Target gene) and Marker type Reference (a) Marker-assisted gene pyramiding Wheat Powdery mildew resistance (Pm2+Pm4a; Pm2+Pm21; Pm4a+Pm21) ; combinations RFLP (Liu et al., 2000) Leaf rust resistance (Lr19 and Lr24);SSR and SCAR (Singh et al., 2017) Leaf rust resistance (Lr19 and Lr24); STS (Singh et al., 2004) FHB resistance (3 QTL); SSR (Miedaner et al., 2006) FHB resistance and DON content (3 QTL); SSR (Wilde et al., 2007) Cereal cyst nematode resistance (CreX and CreY); SCAR (Barloy et al., 2007) FHB resistance (3 QTL); SSR (Wilde et al., 2008) Maize Enrichment of lysine and tryptophan (opaque2 and novel opaque16); umc1066, umc1141 and umc1149 Sarika et al. (2018) Broccoli Diamondback moths resistance (cry1Ac+cry1c) (Cao et al., 2002) Soybean Lepidopteron resistance (cry1Ac+corn earworm QTL) (Walker et al., 2002) Soybean mosaic virus resistance (RSC4, RSC8, and RSC14Q); SSR (Wang et al., 2017) Soybean mosaic virus resistance (Rsv1, Rsv3, and Rsv4); SSR markers (Sat_154 and Satt510) and a gene- specific marker (Rsv1-f/r) (Shi et al., 2009) Soybean rust resistance (Rpp2, Rpp3 and Rpp4); Markers Satt460 and AF162283 Maphosa et al. (2012) Pea Powdery mildew resistance (er1,er2 and Er3) RFLP, RAPD/ SCAR and SSR (Ghafoor & McPhee, 2012) Mung bean Powdery mildew resistance (PMR1, PMR2); RFLP, AFLP (Chaitieng et al., 2002; Humphry et al., 2003; Miyagi et al., 2004) Apple Apple scab resistant (Rvi2, Rvi4, Rvi5, Rvi6, Rvi11, Rvi12, Rvi13, Rvi14 and Rvi15); SSR and SCAR (Patocchi et al., 2009) (b) Marker assisted backcrossing Wheat HMW-glutenins (Glu A1 and Glu-D1 genes); AS-PCR (De Bustos et al., 2001) Fusarium head blight (FHB), orange blossom wheat midge, leaf rust resistance 8 QTL and Sm1 and Lr21 (Somers et al., 2005) Powdery mildew (Pm1c, Pm2, Pm4b, Pm12, Pm13,Pm16, Pm20, Pm21, Pm23, and 13 undocumented genes); AFLP (Zhou et al., 2005) Stripe rust (1 QTL); SSR (Chhuneja et al., 2008) Maize Southwestern corn borer resistance (3 QTL); RFLP (Willcox et al., 2002) ProA enhancement in Sweet corn (lcyE); SSR (Yang et al., 2018) Barley yellow dwarf virus resistance (Yd2); PCR based marker (Jefferies et al., 2003) (c) Marker-assisted validation Wheat FHB resistance (1 QTL);SSR (Pumphrey et al., 2007) Scab resistance (1 QTL); SSR (Zhou et al., 2003) Powdery mildew resistance (3 QTL); SSR (Tucker et al., 2006) Leaf rust resistance (Lr1, Lr9, Lr24,Lr47); STS, SCAR, CAPS (Nocente et al., 2007) (d) Others Tomato Septoria Leaf Spot Resistance (2 inbred lines NC 85L-1W (2007) and NC 839-2(2007)-1); RAPD (Joshi et al., 2015) Tomato mosaic virus (Tm-1, Tm-2, and Tm-22); PCR- based markers (Osei et al., 2019) Powdery mildew resistance (ol-2 gene); RAPD, AFLP (De Giovanni et al., 2004) Potato Potato virus Y resistance (Ryadg gene); RFLP (Hämäläinen et al., 1997) Late blight of potato resistance (R1 gene); RFLP and AFLP (Meksem et al., 1995) Rose Powdery mildew resistance (Single gene Rpp1); AFLPs, RGAs (Linde & Debener, 2003; Linde et al., 2006) Barley Powdery mildew resistance (Mlg resistance locus); RFLP (Kurth et al., 2001) Common bean Anthracnose resistance (gene Are); SCAR, RAPD and RFLP (Adam-Blondon et al., 1994) Apple Powdery mildew resistance (Single gene Pl-w); Isozymes, SCAR, SSR, AFLP, RAPD (Batlle & Alston, 1996; Evans & James, 2003; Hemmat et al., 1994; Liebhard et al., 2002) Table 3. Breeding works on various crops using MAS S. Shrestha; S. Subedi; J. Shrestha Peruvian Journal of Agronomy 4(3): 104–120 (2020) 111 MAS Conventional breeding Marker Assisted Selection aids in determining specific plants with all the resistance alleles imparting more durable multi-genic resistance. Different allele separately imparts same resistance to particular disease which creates confusion in the multi-genic resistance phenotypic selection. Marker Assisted breeding provides an opportunity to discard the plants without desirable allele or alleles in the early stage of their growth by observing the banding pattern after running the gel electrophoresis. Conventional breeding cannot be used to detect desirable trait until the plants’ area well established in the field. Banding patterns can be evaluated for screening the alleles presence that is linked to all those traits. For the improvement of the plant to make it stress tolerance, insect and disease resistance, screening for each trait must be done through separate trials. With the aid of markers, the presence or the absence of concerned allele/alleles can be screened without any particular seasonal consideration. Conventional breeders can improve their cultivar making it cold tolerance only by screening in the cold season that results in lower breeding rate. It is possible to determine allele or alleles associated with the resistance to a specific pest with the use of the markers. Conventional breeding does not allow the screening for the resistance of parasitic pest of another country in own country. Molecular markers aid in undergoing the process of line conversion faster than that of conventional breeding. The process of line conversion is lagged as conventional breeding is incapable in passing recessive desired alleles into subsequent generation as quickly as with the aid of markers since breeders cannot identify heterozygous plant phenotypically and should undergo selfing several times for its accomplishment. Table 4. Differences between MAS and Conventional breeding (Dreher et al., 2002) Figure 3: Comparison between conventional backcrossing and background selection during marker assisted backcrossing (Rani et al., 2014) Conventional back crossing Marker-assisted back crossing Marker-assisted selection: a smart biotechnological strategy for modern plant breeding. September - December 2020 112 The comparison between conventional backcrossing and background selection during marker assisted backcrossing is given in Figure 3. The advantages and disadvantages of MAS and conventional breeding is given in Table 5. Importance of MAS It makes efficient use of glasshouse or nursery making the selection possible in the seedling stage as several lines can be discarded early in the breeding scheme which is non-profitable. MAS allows a single selection of plants as screening is carried out using markers that eliminate error due to environmental factors. MAS is not affected by environmental factors and allows for the determination of certain traits (resistance to disease, insect, abiotic stress) independent of the environment as indirect selection of traits is done with the use of markers (Osei et al., 2019). It can even save breeders time, resources, and effort. It also aids in the enhancement of the heterosis, high- density linkage maps construction. Genetic contribution of each parent to its each progeny can also be determined with the aid of marker assisted selection and enables the effective selection for horizontal resistance. RFLP and SSR/microsatellites are co-dominant markers which are technically simple, reliable, robust, and transferable between populations (Kochert, 1994; McCouch et al., 1997; Tanksley et al., 1989). RAPD and AFLP are dominant markers which are quick, simple, a small amount of DNA required and have possibility of multiple loci and generation of the high level of polymorphism respectively (Vos et al., 1995; Welsh & McClelland, 1990; Williams et al., 1991). Marker assisted selection helps in genes pyramiding and also makes backcrossing more efficient. It helps in visualizing the loci for quantitative resistance and compilation of QTLs from different donors into one genotype to promote the level of quantitative resistance. Desirable allele can be recognized in the initial stage as reported for QPM; mutant opaque2 allele can be spotted with the increase in the level of lysine and tryptophan in the kernel in the initial stage of plant growth before the visibility of its reproductive life that will ultimately be economic (Dreher et al., 2002). Stress Resistant and Quality of Rice can be obtained with the aid of marker assisted selection through gene stacking (Das et al., 2017). When recessive alleles governs the trait of our interest but it’s challenging enough to detect that alleles from phenotypic evaluation of heterozygous plant and from the traditional backcrossing method as it turns out to be time and resource consuming; MAS makes our work much easier for the detection of recessive alleles with the application of the markers linked with them. Advantages Disadvantages (a) Marker Assisted Selection (MAS) It involves genotypic selection of traits of interest of plants through the use of molecular markers. This method is expensive in genotyping large number of plants. It helps to maintain high level of genetic purity through cultural identification. There may be low level of recombination between marker and QTL resulting in the need of flanking markers. It is useful for genetic diversity assessment and selection of parents. It is still not widely used due to less researches, published papers, knowledge gap and limited polymorphic markers. Marker assisted backcrossing helps to reduce linkage drag and parent’s genotype can be reconstructed in three generations. Marker assisted backcrossing is capable of refining only the existing elite genotypes of plants. Pyramiding of desirable genes is easy, fast and an early stage screening is possible. There may arise the problem in the exact determination of position and effect of QTL. Poor heritability and environmental factors do not create problem. It cannot predict phenotype with 100 percent reliability. (b) Conventional breeding It is being used widely in the development of cultivars. Its phenotypic selection resulting in longer time to develop superior variety. It is simple and easy as there is no need of consideration of QTL and target gene. It requires to undergo ‘grow-out tests’ for the assessment of purity. Publications of researches based on it are easily available. It doesn’t deal with the genetic diversity and it is difficult to distinguish homozygous and heterozygous plants just from the phenotype. It is breeder-friendly. Recurrent parent genotype reconstruction takes more than six generations. It is cheap and more reliable method. Time consuming and hard to test phenotypically the presence of more than one gene. Table 5. Advantages and Disadvantages of MAS and Conventional breeding (Lema, 2018) S. Shrestha; S. Subedi; J. Shrestha Peruvian Journal of Agronomy 4(3): 104–120 (2020) 113 Limitations of MAS Markers may not be useful for every trait as an effective phenotyping method already exist which is less expensive than MAS. The type of information that is required for conducting QTL validation and mapping has a limited number of published reports. It is an expensive method as it includes large start-up expenses, licensing costs, maintenance costs, etc. There are limited markers with limited polymorphism. Like, the SSR marker in wheat was utilized for indication of the Sr2 gene responsible for stem rust resistance for all except for four Australian cultivars which is susceptible to it (Spielmeyer et al., 2003). Sometimes there is insufficient linkage between markers and genes. Recombination events may occur between the gene of our interest and marker used which may lead to false positive. While conducting MAS, the interaction between quantitative trait loci and environmental effects are not considered. Markers that are developed for MAS may be valid for one population and may not be valid for the other. Knowledge gap between molecular biology experts and the breeder creates the problem in the understanding of the concepts and the language used by the expert (Collard et al., 2005). There is also inadequate coordination between different researchers and plant breeders. Conclusion The scope of Marker Assisted Selection is going to be wider as more and more genes are identified and their functions and interactions are annotated. MAS is used to accelerate the recurrent parents’ retrieval with the aid of molecular backcrossing. The use of markers that flank a target gene can minimize the number of backcross generations. MAS technology has been successfully utilized for the breeding of disease-resistant crops. Rice yield is subjected to severe losses due to adverse effect of a number of stress factors; utilization of tolerant/resistant cultivars is the most effective method of controlling reduced crop production. Through the process of gene pyramiding, multiple stress resistant genes could be incorporated into a single rice variety in order to develop a rice variety with high yield, biotic stress resistance and abiotic stress tolerance along with enhanced nutritional quality. References Abler, B. S. B., Edwards, M. D., & Stuber, C. W. (1991). Isoenzymatic identification of quantitative trait loci in crosses of elite maize inbreds. Crop Science, 31(2), 267–274. https://doi.org/10.2135/ cropsci1991.0011183X003100020006x Adam-Blondon, A.-F., Sévignac, M., Bannerot, H., & Dron, M. (1994). SCAR, RAPD and RFLP markers linked to a dominant gene (Are) conferring resistance to anthracnose in common bean. Theoretical and Applied Genetics, 88(6–7), 865–870. https://doi. org/10.1007/BF01253998 Al-Samarai, F., & Al-Kazaz, A. (2015). Molecular Markers: an Introduction and Applications. European Journal of Molecular Biotechnology, 9. https://doi. org/10.13187/ejmb.2015.9.118 Arshad, H. M. I., Sahi, S. T., Atiq, M., & Wakil, W. (2016). Appraisal of resistant genes and gene pyramid lines of rice against indigenous pathotypes of Xanthomonas oryzae pv. oryzae in Punjab, Pakistan. Pakistan Journal of Agricultural Sciences, 53(2), 365–370. https://doi.org/10.21162/PAKJAS/16.5357 Arunakumari, K., Durgarani, C. V, Satturu, V., Sarikonda, K. R., Chittoor, P. D. R., Vutukuri, B., Laha, G. S., Nelli, A. P. K., Gattu, S., & Jamal, M. (2016). Marker- assisted pyramiding of genes conferring resistance against bacterial blight and blast diseases into Indian rice variety MTU1010. Rice Science, 23(6), 306– 316. https://doi.org/10.1016/j.rsci.2016.04.005 Barloy, D., Lemoine, J., Abelard, P., Tanguy, A.-M., Rivoal, R., & Jahier, J. (2007). Marker-assisted pyramiding of two cereal cyst nematode resistance genes from Aegilops variabilis in wheat. Molecular Breeding, 20(1), 31–40. https://doi.org/10.1007/s11032-006- 9070-x Batlle, I., & Alston, F. H. (1996). Genes determining leucine aminopeptidase and mildew resistance from the ornamental apple,‘White Angel.’ Theoretical and Applied Genetics, 93(1–2), 179–182. https://doi. org/10.1007/BF00225743 Bottema, C. D. K., Sarkar, G., Cassady, J. D., Ii, S., Dutton, C. M., & Sommer, S. S. (1993). [29] Polymerase chain reaction amplification of specific alleles: A general method of detection of mutations, polymorphisms, and haplotypes. Methods in Enzymology, 218, 388–402. Elsevier. https://doi.org/10.1016/0076- 6879(93)18031-7 Caetano-Anollés, G., Brant J., B., & Peter M., G. (1991). DNA Amplification Fingerprinting Using Very Short Arbitrary Oligonucleotide Primers. Bio/Technology, 9(6), 553–557. https://doi.org/10.1038/nbt0691-553 Cao, J., Zhao, J.-Z., Tang, J., Shelton, A., & Earle, E. (2002). Broccoli plants with pyramided cry1Ac and cry1C Bt genes control diamondback moths resistant to Cry1A and Cry1C proteins. Theoretical and Applied Genetics, 105(2–3), 258–264. https://doi. org/10.1007/s00122-002-0942-0 Castro, A. J., Capettini, F., Corey, A. E., Filichkina, T., Hayes, P. M., Kleinhofs, A., Kudrna, D., Richardson, K., Sandoval-Islas, S., & Rossi, C. (2003). Mapping Marker-assisted selection: a smart biotechnological strategy for modern plant breeding. September - December 2020 114 and pyramiding of qualitative and quantitative resistance to stripe rust in barley. Theoretical and Applied Genetics, 107(5), 922–930. https://doi. org/10.1007/s00122-003-1329-6 Chaitieng, B., Kaga, A., Han, O. K., Wang, X. W., Wongkaew, S., Laosuwan, P., Tomooka, N., & Vaughan, D. A. (2002). Mapping a new source of resistance to powdery mildew in mungbean. Plant Breeding, 121(6), 521–525. https://doi.org/10.1046/ j.1439-0523.2002.00751.x Chhuneja, P., Kaur, S., Garg, T., Ghai, M., Kaur, S., Prashar, M., Bains, N. S., Goel, R. K., Keller, B., & Dhaliwal, H. S. (2008). Mapping of adult plant stripe rust resistance genes in diploid A genome wheat species and their transfer to bread wheat. Theoretical and Applied Genetics, 116(3), 313–324. https://doi. org/10.1007/s00122-007-0668-0 Chu, Z., Yuan, M., Yao, J., Ge, X., Yuan, B., Xu, C., Li, X., Fu, B., Li, Z., & Bennetzen, J. L. (2006). Promoter mutations of an essential gene for pollen development result in disease resistance in rice. Genes & Development, 20(10), 1250–1255. https:// doi.org/10.1101/gad.1416306 Chukwu, S. C., Rafii, M. Y., Ramlee, S. I., Ismail, S. I., Oladosu, Y., Okporie, E., Onyishi, G., Utobo, E., Ekwu, L., Swaray, S., & Jalloh, M. (2019). Marker- assisted selection and gene pyramiding for resistance to bacterial leaf blight disease of rice (Oryza sativa L.). Biotechnology & Biotechnological Equipment, 33(1), 440–455. https://doi.org/10.1080/13102818.2 019.1584054 Collard, B. C.Y., Jahufer, M. Z. Z., Brouwer, J. B., & Pang, E. C. K. (2005). An introduction to markers, quantitative trait loci (QTL) mapping and marker- assisted selection for crop improvement: The basic concepts. Euphytica, 142(1–2), 169–196. https://doi. org/10.1007/s10681-005-1681-5 Collard, Bertrand C.Y., & Mackill, D. J. (2008). Marker- assisted selection: An approach for precision plant breeding in the twenty-first century. Philosophical Transactions of the Royal Society B: Biological Sciences, 363(1491), 557–572. https://doi. org/10.1098/rstb.2007.2170 Das, G., & Rao, G. J. N. (2015). Molecular marker assisted gene stacking for biotic and abiotic stress resistance genes in an elite rice cultivar. Frontiers in Plant Science, 6(September), 1–18. https://doi. org/10.3389/fpls.2015.00698 Das, G., Patra, J. K., & Baek, K. H. (2017). Insight into MAS: A molecular tool for development of stress resistant and quality of rice through gene stacking. Frontiers in Plant Science, 8(June), 1–9. https://doi. org/10.3389/fpls.2017.00985 De Bustos, A., Rubio, P., Soler, C., Garcia, P., & Jouve, N. (2001). Marker assisted selection to improve HMW-glutenins in wheat. In Wheat in a Global environment (pp. 171–176). Springer. https://doi. org/10.1007/978-94-017-3674-9_19 De Giovanni, C., Dell’Orco, P., Bruno, A., Ciccarese, F., Lotti, C., & Ricciardi, L. (2004). Identification of PCR-based markers (RAPD, AFLP) linked to a novel powdery mildew resistance gene (ol-2) in tomato. Plant Science, 166(1), 41–48. https://doi. org/10.1016/j.plantsci.2003.07.005 Divya, B., Robin, S., Rabindran, R., Senthil, S., Raveendran, M., & Joel, A. J. (2014). Marker assisted backcross breeding approach to improve blast resistance in Indian rice (Oryza sativa) variety ADT43. Euphytica, 200(1), 61–77. https://doi. org/10.1007/s10681-014-1146-9 Dixit, S., Yadaw, R. B., Mishra, K. K., & Kumar, A. (2017). Marker-assisted breeding to develop the drought-tolerant version of Sabitri, a popular variety from Nepal. Euphytica, 213(8), 184. https://doi. org/10.1007/s10681-017-1976-3 Dreher, K., Morris, M., Khairallah, M., Ribaut, J.-M., Pandey, S., & Srinivasan, G. (2002). Is marker- assisted selection cost-effective compared to conventional plant breeding methods? The case of quality protein maize. Proceedings of the 4th Annual Conference of the International Consortium on Agricultural Biotechnology Research (ICABR’00), 203–236. Evans, K., & James, C. (2003). Identification of SCAR markers linked to Pl-w mildew resistance in apple. Theoretical and Applied Genetics, 106(7), 1178– 1183. https://doi.org/10.1007/s00122-002-1147-2 Ghafoor, A., & McPhee, K. (2012). Marker assisted selection (MAS) for developing powdery mildew resistant pea cultivars. Euphytica, 186(3), 593–607. https://doi.org/10.1007/s10681-011-0596-6 Gupta, P. K., Langridge, P., & Mir, R. R. (2010). Marker- assisted wheat breeding: Present status and future possibilities. Molecular Breeding, 26(2), 145–161. https://doi.org/10.1007/s11032-009-9359-7 Hämäläinen, J. H., Watanabe, K. N., Valkonen, J. P. T., Arihara, A., Plaisted, R. L., Pehu, E., Miller, L., & Slack, S. A. (1997). Mapping and marker-assisted selection for a gene for extreme resistance to potato virus Y. Theoretical and Applied Genetics, 94(2), 192–197. Hasan, M., Rafii, M., Ismail, M., Mahmood, M., Rahim, H., Alam, M. A., Ashkani, S., Malek, M., & A., L. (2015). Marker-assisted backcrossing: A useful method for rice improvement. Biotechnology & S. Shrestha; S. Subedi; J. Shrestha Peruvian Journal of Agronomy 4(3): 104–120 (2020) 115 Biotechnological Equipment, 29, 1–18. https://doi.or g/10.1080/13102818.2014.995920 Hayashi, K., Yoshida, H., & Ashikawa., I. (2006). Development of PCR–based allele specific and InDel marker sets for nine rice blast resistance genes. Theoretical and Applied Genetics, 113, 251–260. Heikrujam, M., Sharma, K., Kumar, J., & Agrawal, V. (2014). Generation and validation of unique male sex-specific sequence tagged sites (STS) marker from diverse genotypes of dioecious Jojoba-Simmondsia chinensis (Link) Schneider. Euphytica, 199(3), 363– 372. https://doi.org/10.1007/s10681-014-1136-y Hemmat, M., Weedon, N. F., Manganaris, A. G., & Lawson, D. M. (1994). Molecular marker linkage map for apple. Journal of Heredity, 85(1), 4–11. https://doi. org/10.1093/oxfordjournals.jhered.a111390 Hittalmani, S., Parco, A., Mew, T. V, Zeigler, R. S., & Huang, N. (2000). Fine mapping and DNA marker- assisted pyramiding of the three major genes for blast resistance in rice. Theoretical and Applied Genetics, 100(7), 1121–1128. https://doi.org/10.1007/ s001220051395 Holland, J. B. (2004). Implementation of molecular markers for quantitative traits in breeding programs- challenges and opportunities. New Directions for a Diverse Planet: Proceedings for the 4th International Crop Science Congress. Regional Institute, Gosford, Australia, Www. Cropscience. Org. Au/Icsc2004. https://doi.org/10.5897/BMBR2010.0006 Hu, J., Li, X., Wu, C., Yang, C., Hua, H., Gao, G., Xiao, J., & He, Y. (2012). Pyramiding and evaluation of the brown planthopper resistance genes Bph14 and Bph15 in hybrid rice. Molecular Breeding, 29(1), 61–69. https://doi.org/10.1007/s11032-010-9526-x Humphry, M. E., Magner, T., McIntyre, C. L., Aitken, E. A. B., & Liu, C. J. (2003). Identification of a major locus conferring resistance to powdery mildew (Erysiphe polygoni DC) in mungbean (Vigna radiata L. Wilczek) by QTL analysis. Genome, 46(5), 738– 744. https://doi.org/10.1139/g03-057 Jamaloddin, M., Durga Rani, C. V., Swathi, G., Anuradha, C., Vanisri, S., Rajan, C. P. D., Krishnam Raju, S., Bhuvaneshwari, V., Jagadeeswar, R., Laha, G.S., Prasad, M.S., Satyanarayana, P.V., Cheralu, C., Rajani, G., Ramprasad, E., Sravanthi, P., Arun Prem Kumar, N., Aruna Kumari, K., ..... Sheshu Madhav, M. (2020). Marker Assisted Gene Pyramiding (MAGP) for bacterial blight and blast resistance into mega rice variety “Tellahamsa”. PloS one, 15(6), e0234088. https://doi.org/10.1371/ journal.pone.0234088 Jefferies, S. P., King, B. J., Barr, A. R., Warner, P., Logue, S. J., & Langridge, P. (2003). Marker‐ assisted backcross introgression of the Yd2 gene conferring resistance to barley yellow dwarf virus in barley. Plant Breeding, 122(1), 52–56. https://doi. org/10.1046/j.1439-0523.2003.00752.x Ji, Z., Shi, J., Zeng, Y., Qian, Q., & Yang, C. (2014). Application of a simplified marker-assisted backcross technique for hybrid breeding in rice. Biologia (Poland), 69(4), 463–468. https://doi.org/10.2478/ s11756-014-0335-2 Jones J.D.G. , & Dangl J.L. (2006). The plant immune system. Nature, 444, 323–329. Joshi, B. K., Louws, F. J., Yenco, G. C., Sosinski, B. R., Arellano, C., & Panthee, D. R. (2015). Molecular Markers for Septoria Leaf Spot (Septoria lycopersicii Speg.) Resistance in Tomato (Solanum lycopersicum L.). Nepal Journal of Biotechnology, 3(1), 40–47. https://doi.org/10.3126/njb.v3i1.14230 Joshi, R. K., & Nayak, S. (2010). Gene pyramiding-A broad spectrum technique for developing durable stress resistance in crops. Biotechnology and Molecular Biology Reviews, 5(3), 51-60. K. Osei, M., Prempeh, R., Adjebeng-Danquah, J., A. Opoku, J., Danquah, A., Danquah, E., Blay, E., & Adu-Dapaah, H. (2019). Marker-Assisted Selection (MAS): A Fast-Track Tool in Tomato Breeding. Recent Advances in Tomato Breeding and Production. https://doi.org/10.5772/intechopen.76007 Kausar, S., Hameed, S., Saleem, K., ul Haque, I., Zamurrad, M., & Ashfaq, M. (2015). Molecular confirmation of Bdv2 gene in wheat germplasm and its field based assessment for resistance against barely yellow dwarf viruses. Advancements in Life Sciences, 3(1), 16–22. Kelly, J. D., Gepts, P., Miklas, P. N., & Coyne, D. P. (2003). Tagging and mapping of genes and QTL and molecular marker-assisted selection for traits of economic importance in bean and cowpea. Field Crops Research, 82(2–3), 135–154. https://doi. org/10.1016/S0378-4290(03)00034-0 Khan, G. H., Shikari, A. B., Vaishnavi, R., Najeeb, S., Padder, B. A., Bhat, Z. A., Parray, G. A., Bhat, M. A., Kumar, R., & Singh, N. K. (2018). Marker-assisted introgression of three dominant blast resistance genes into an aromatic rice cultivar Mushk Budji. Scientific Reports, 8(1), 4091. https://doi.org/10.1038/s41598- 018-22246-4 Kim, S.-M., Suh, J.-P., Qin, Y., Noh, T.-H., Reinke, R. F., & Jena, K. K. (2015). Identification and fine-mapping of a new resistance gene, Xa40, conferring resistance Marker-assisted selection: a smart biotechnological strategy for modern plant breeding. September - December 2020 116 to bacterial blight races in rice (Oryza sativa L.). Theoretical and Applied Genetics, 128(10), 1933– 1943. https://doi.org/10.1007/s00122-015-2557-2 Kloppers, F. J., & Pretorius, Z. A. (1997). Effects of combinations amongst genes Lr13, Lr34 and Lr37 on components of resistance in wheat to leaf rust. Plant Pathology, 46(5), 737–750. https://doi. org/10.1046/j.1365-3059.1997.d01-58.x Kochert, G. (1994). RFLP technology. In DNA-based markers in plants (pp. 8–38). Springer. https://doi. org/10.1007/978-94-011-1104-1_2 Kottapalli, K. R., Narasu, M. L., & Jena, K. K. (2010). Effective strategy for pyramiding three bacterial blight resistance genes into fine grain rice cultivar, Samba Mahsuri, using sequence tagged site markers. Biotechnology letters, 32(7), 989-996. https://doi.org/10.1007/s10529-010-0249-1 Kumar, N. S., & Gurusubramanian, G. (2011). Random amplified polymorphic DNA (RAPD) markers and its applications. Science Vision, 11(3), 116–124. Kumar, V. A., Balachiranjeevi, C. H., Naik, S. B., Rambabu, R., Rekha, G., Madhavi, K. R., Harika, G., Vijay, S., Pranathi, K., Hajira, S. K., Srivastava, A., Mahadevaswamy, H. K., Anila, M., Yugander, A., Aruna, J., Prasad, A. S. H., Madhav, M. S., Laha, G. S., Viraktamath, B. C., & Prasad, M. S. (2016). Marker-assisted introgression of the major bacterial blight resistance gene, Xa21 and blast resistance gene, Pi54 into RPHR-1005, the restorer line of the popular rice hybrid, DRRH3. Journal of Plant Biochemistry and Biotechnology, 25(4), 400–409. https://doi.org/10.1007/s13562-016-0352-z Kumar, V. A., Balachiranjeevi, C. H., Naik, S. B., Rekha, G., Rambabu, R., Harika, G., ... & Kale, R. (2017). Marker-assisted pyramiding of bacterial blight and gall midge resistance genes into RPHR-1005, the restorer line of the popular rice hybrid DRRH- 3. Molecular Breeding, 37(7), 86. https://doi. org/10.1007/s11032-017-0687-8 Kurokawa, Y., Noda, T., Yamagata, Y., Angeles-Shim, R., Sunohara, H., Uehara, K., ... & Yoshimura, A. (2016). Construction of a versatile SNP array for pyramiding useful genes of rice. Plant Science, 242, 131-139. https://doi.org/10.1016/j.plantsci.2015.09.008 Kurth, J., Kolsch, R., Simons, V., & Schulze-Lefert, P. (2001). A high-resolution genetic map and a diagnostic RFLP marker for the Mlg resistance locus to powdery mildew in barley. Theoretical and Applied Genetics, 102(1), 53–60. https://doi. org/10.1007/s001220051617 Lema, M. (2018). Marker Assisted Selection in Comparison to Conventional Plant Breeding: Review Article. Agricultural Research and Technology: Open Access Journal, 14(2). https://doi.org/10.19080/ artoaj.2018.14.555914 Liebhard, R., Gianfranceschi, L., Koller, B., Ryder, C. D., Tarchini, R., Van de Weg, E., & Gessler, C. (2002). Development and characterisation of 140 new microsatellites in apple (Malus x domestica Borkh.). Molecular Breeding, 10(4), 217–241. https://doi. org/10.1023/A:1020525906332 Linde, M., & Debener, T. (2003). Isolation and identification of eight races of powdery mildew of roses (Podosphaera pannosa)(Wallr.: Fr.) de Bary and the genetic analysis of the resistance gene Rpp1. Theoretical and Applied Genetics, 107(2), 256–262. https://doi.org/10.1007/s00122-003-1240-1 Linde, M., Hattendorf, A., Kaufmann, H., & Debener, T. (2006). Powdery mildew resistance in roses: QTL mapping in different environments using selective genotyping. Theoretical and Applied Genetics, 113(6), 1081–1092. https://doi.org/10.1007/s00122- 006-0367-2 Liu, J., Liu, D., Tao, W., Li, W., Wang, S., Chen, P., Cheng, S., & Gao, D. (2000). Molecular marker‐facilitated pyramiding of different genes for powdery mildew resistance in wheat. Plant Breeding, 119(1), 21–24. https://doi.org/10.1046/j.1439-0523.2000.00431.x Mackill, D. J., Nguyen, H. T., & Zhang, J. (1999). Use of molecular markers in plant improvement programs for rainfed lowland rice. Field Crops Research, 64(1), 177–185. https://doi.org/10.1016/S0378- 4290(99)00058-1 Malav, A. K., Indu., & Chandrawat, K. S. (2016). Gene pyramiding: An overview. International Journal of Current Research in Biosciences and Plant Biology, 3, 22–28. http://dx.doi.org/10.20546/ ijcrbp.2016.307.004 Maphosa, M., Talwana, H., & Tukamuhabwa, P. (2012). Enhancing soybean rust resistance through Rpp2, Rpp3 and Rpp4 pair wise gene pyramiding. African Journal of Agricultural Research, 7(30), 4271–4277. McCouch, S. R., Chen, X., Panaud, O., Temnykh, S., Xu, Y., Cho, Y. G., Huang, N., Ishii, T., & Blair, M. (1997). Microsatellite marker development, mapping and applications in rice genetics and breeding. In Oryza: From Molecule to Plant (pp. 89–99). Springer. https://doi.org/10.1007/978-94-011-5794-0_9 McCough, S. R., & Doerge, R. W. (1995). QTL mapping in rice. Trends in Genetics, 11(12), 482–487. https:// doi.org/10.1016/S0168-9525(00)89157-X Mehlenbacher, S. A. (1995). Classical and molecular approaches to breeding fruit and nut crops for disease resistance. HortScience, 30(3), 466–477. S. Shrestha; S. Subedi; J. Shrestha Peruvian Journal of Agronomy 4(3): 104–120 (2020) 117 Meksem, K., Leister, D., Peleman, J., Zabeau, M., Salamini, F., & Gebhardt, C. (1995). A high-resolution map of the vicinity of the R1 locus on chromosome V of potato based on RFLP and AFLP markers. Molecular and General Genetics MGG, 249(1), 74–81. https:// doi.org/10.1007/BF00290238 Miedaner, T., Wilde, F., Steiner, B., Buerstmayr, H., Korzun, V., & Ebmeyer, E. (2006). Stacking quantitative trait loci (QTL) for Fusarium head blight resistance from non-adapted sources in an European elite spring wheat background and assessing their effects on deoxynivalenol (DON) content and disease severity. Theoretical and Applied Genetics, 112(3), 562–569. Miyagi, M., Humphry, M., Ma, Z. Y., Lambrides, C. J., Bateson, M., & Liu, C. J. (2004). Construction of bacterial artificial chromosome libraries and their application in developing PCR-based markers closely linked to a major locus conditioning bruchid resistance in mungbean (Vigna radiata L. Wilczek). Theoretical and Applied Genetics, 110(1), 151–156. https://doi.org/10.1007/s00122-004-1821-7 Mohan, M., Nair, S., Bhagwat, A., Krishna, T. G., Yano, M., Bhatia, C. R., & Sasaki, T. (1997). Genome mapping, molecular markers and marker-assisted selection in crop plants. Molecular Breeding, 3(2), 87–103. https://doi.org/10.1023/A:1009651919792 Nadeem, M. A., Nawaz, M. A., Shahid, M. Q., Doğan, Y., Comertpay, G., Yıldız, M., Hatipoğlu, R., Ahmad, F., Alsaleh, A., Labhane, N., Özkan, H., Chung, G., & Baloch, F. S. (2018). DNA molecular markers in plant breeding: current status and recent advancements in genomic selection and genome editing. Biotechnology & Biotechnological Equipment, 32(2), 261–285. https://doi.org/10.1080 /13102818.2017.1400401 Niño-Liu D.O., Ronald P.C., & Bogdanove A.J. (2006). Xanthomonas oryzae pathovars: Model pathogen of a model crop. Molecular Plant Pathology, 7, 303– 324. Nocente, F., Gazza, L., & Pasquini, M. (2007). Evaluation of leaf rust resistance genes Lr1, Lr9, Lr24, Lr47 and their introgression into common wheat cultivars by marker-assisted selection. Euphytica, 155(3), 329– 336. https://doi.org/10.1007/s10681-006-9334-x Nogoy, F. M., Song, J.-Y., Ouk, S., Rahimi, S., Kwon, S. W., Kang, K.-K., & Cho, Y.-G. (2016). Current Applicable DNA Markers for Marker Assisted Breeding in Abiotic and Biotic Stress Tolerance in Rice (Oryza sativa L.) . Plant Breeding and Biotechnology, 4(3), 271–284. https://doi. org/10.9787/pbb.2016.4.3.271 Ogbonnaya, F. C., Subrahmanyam, N. C., Moullet, O., De Majnik, J., Eagles, H. A., Brown, J. S., Eastwood, R. F., Kollmorgen, J., Appels, R., & Lagudah, E. S. (2001). Diagnostic DNA markers for cereal cyst nematode resistance in bread wheat. Australian Journal of Agricultural Research, 52(12), 1367– 1374. https://doi.org/10.1071/AR01031 Panaud, O., Chen, X., & McCouch, S. R. (1996). Development of microsatellite markers and characterization of simple sequence length polymorphism (SSLP) in rice (Oryza sativa L.). Molecular and General Genetics MGG, 252(5), 597–607. https://doi.org/10.1007/BF02172406 Patocchi, A., Frei, A., Frey, J. E., & Kellerhals, M. (2009). Towards improvement of marker assisted selection of apple scab resistant cultivars: Venturia inaequalis virulence surveys and standardization of molecular marker alleles associated with resistance genes. Molecular Breeding, 24(4), 337. https://doi. org/10.1007/s11032-009-9295-6 Patroti, P., Vishalakshi, B., Umakanth, B., Suresh, J., Senguttuvel, P., & Madhav, M. S. (2019). Marker- assisted pyramiding of major blast resistance genes in Swarna-Sub1, an elite rice variety (Oryza sativa L.). Euphytica, 215(11). https://doi.org/10.1007/ s10681-019-2487-1 Pradhan, S. K., Nayak, D. K., Mohanty, S., Behera, L., Barik, S. R., Pandit, E., Lenka, S., & Anandan, A. (2015). Pyramiding of three bacterial blight resistance genes for broad-spectrum resistance in deepwater rice variety, Jalmagna. Rice, 8(1), 19. https://doi.org/10.1186/s12284-015-0051-8 Pumphrey, M. O., Bernardo, R., & Anderson, J. A. (2007). Validating the Fhb1 QTL for Fusarium head blight resistance in near‐isogenic wheat lines developed from breeding populations. Crop Science, 47(1), 200– 206. https://doi.org/10.2135/cropsci2006.03.0206 Ramalingam, J., Savitha, P., Alagarasan, G., Saraswathi, R., & Chandrababu, R. (2017). Functional marker assisted improvement of stable cytoplasmic male sterile lines of rice for bacterial blight resistance. Frontiers in Plant Science, 8(June), 1–9. https://doi. org/10.3389/fpls.2017.01131 Rana, M., Sood, A., Hussain, W., Kaldate, R., Sharma, T.R., Gill, R.K., Kumar, S., & Singh, S. (2019). Gene pyramiding and multiple character breeding. In Lentils. pp. 83-124. Academic Press. Rani, P. J., Satyanarayana, P. V., Chamundeswari, N., & Rani, M. G. (2014). A review on marker assisted selection in crop improvement. https://www. semanticscholar.org/paper/Review-article-A- REVIEW-ON-MARKER-ASSISTED-IN-CROP- Rani-Satyanarayana/6b036be9086540c5193c70633 c95a8bee68d7ee5 Marker-assisted selection: a smart biotechnological strategy for modern plant breeding. September - December 2020 118 Ranade, S. A., Srivastava, A. P., Rana, T. S., Srivastava, J., & Tuli, R. (2008). Easy assessment of diversity in Jatropha curcas L. plants using two single- primer amplification reaction (SPAR) methods. Biomass and Bioenergy, 32(6), 533–540. https://doi. org/10.1016/j.biombioe.2007.11.006 Sarika, K., Hossain, F., Muthusamy, V., Zunjare, R. U., Baveja, A., Goswami, R., Bhat, J. S., Saha, S., & Gupta, H. S. (2018). Marker-assisted pyramiding of opaque2 and novel opaque16 genes for further enrichment of lysine and tryptophan in sub-tropical maize. Plant Science, 272, 142–152. Schütte, U. M. E., Abdo, Z., Bent, S. J., Shyu, C., Williams, C. J., Pierson, J. D., & Forney, L. J. (2008). Advances in the use of terminal restriction fragment length polymorphism (T-RFLP) analysis of 16S rRNA genes to characterize microbial communities. Applied Microbiology and Biotechnology, 80(3), 365–380. https://doi.org/10.1007/s00253-008-1565- 4 Servin, B., Martin, O. C., & Mézard, M. (2004). Toward a theory of marker-assisted gene pyramiding. Genetics, 168(1), 513–523. https://doi.org/10.1534/ genetics.103.023358 Shanti, M. L., George, M. L. C., Cruz, C. M. V., Bernardo, M. A., Nelson, R. J., Leung, H., Reddy, J. N., & Sridhar, R. (2001). Identification of resistance genes effective against rice bacterial blight pathogen in eastern India. Plant Disease, 85(5), 506–512. https:// doi.org/10.1094/PDIS.2001.85.5.506 Shavrukov, Y. N. (2016). CAPS markers in plant biology. Russian Journal of Genetics: Applied Research, 6(3), 279–287. https://doi.org/10.1134/ S2079059716030114 Shi, A., Chen, P., Li, D., Zheng, C., Zhang, B., & Hou, A. (2009). Pyramiding multiple genes for resistance to soybean mosaic virus in soybean using molecular markers. Molecular Breeding, 23(1), 113. https://doi. org/10.1007/s11032-008-9219-x Singh S., Sidhu J.S., Huang N., Vikal Y., Li Z., Brar D.S., Dhaliwal H.S., & Khush G.S. (2001). Pyramiding three bacterial blight resistance genes (xa5, xa13 and Xa21) using marker assisted selection into indica rice cultivar PR106. Theoretical and Applied Genetics, 102, 1011–1015. Singh, M., Mallick, N., Chand, S., Kumari, P., Sharma, J. B., Sivasamy, M., Jayaprakash, P., Prabhu, K. V, & Jha, S. K. (2017). Marker-assisted pyramiding of Thinopyrum-derived leaf rust resistance genes Lr19 and Lr24 in bread wheat variety HD2733. Journal of Genetics, 96(6), 951–957. Singh, R., Datta, D., Singh, S., & Tiwari, R. (2004). Marker- assisted selection for leaf rust resistance genes Lr19 and Lr24 in wheat (Triticum aestivum L.). Journal of Applied Genetics, 45(4), 399–404. Singh, S., Sidhu, J. S., Huang, N., Vikal, Y., Li, Z., Brar, D. S., Dhaliwal, H. S., & Khush, G. S. (2001). Pyramiding three bacterial blight resistance genes (xa5, xa13 and Xa21) using marker-assisted selection into indica rice cultivar PR106. Theoretical and Applied Genetics, 102(6–7), 1011–1015. https:// doi.org/10.1007/s001220000495 Snowdon, R. J., & Friedt, W. (2004). Molecular markers in Brassica oilseed breeding: current status and future possibilities. Plant Breeding, 123(1), 1–8. https:// doi.org/10.1111/j.1439-0523.2003.00968.x Somers, D. J., Thomas, J., DePauw, R., Fox, S., Humphreys, G., & Fedak, G. (2005). Assembling complex genotypes to resist Fusarium in wheat (Triticum aestivum L.). Theoretical and Applied Genetics, 111(8), 1623–1631. https://doi.org/10.1007/s00122- 005-0094-0 Spielmeyer, W., Sharp, P. J., & Lagudah, E. S. (2003). Identification and validation of markers linked to broad‐spectrum stem rust resistance gene Sr2 in wheat (Triticum aestivum L.). Crop Science, 43(1), 333–336. https://doi.org/10.2135/cropsci2003.3330 Sun, X., Cao, Y., Yang, Z., Xu, C., Li, X., Wang, S., & Zhang, Q. (2004). Xa26, a gene conferring resistance to Xanthomonas oryzae pv. oryzae in rice, encodes an LRR receptor kinase‐like protein. The Plant Journal, 37(4), 517–527. https://doi.org/10.1046/ j.1365-313X.2003.01976.x Swathi, G., Durga Rani, C. V., Md, J., Madhav, M. S., Vanisree, S., Anuradha, C., Kumar, N. R., Kumar, N. A. P., Kumari, K. A., Bhogadhi, S. C., Ramprasad, E., Sravanthi, P., Raju, S. K., Bhuvaneswari, V., Rajan, C. P. D., & Jagadeeswar, R. (2019). Marker- assisted introgression of the major bacterial blight resistance genes, Xa21 and xa13, and blast resistance gene, Pi54, into the popular rice variety, JGL1798. Molecular Breeding, 39(4). https://doi.org/10.1007/ s11032-019-0950-2 Tabien, R. E., Li, Z., Paterson, A. H., Marchetti, M. A., Stansel, J. W., Pinson, S. R. M., & Park, W. D. (2000). Mapping of four major rice blast resistance genes from’Lemont’and’Teqing’and evaluation of their combinatorial effect for field resistance. Theoretical and Applied Genetics, 101(8), 1215–1225. https:// doi.org/10.1007/s001220051600 Tanksley, S. D., Young, N. D., Paterson, A. H., & Bonierbale, M. W. (1989). RFLP mapping in plant breeding: new S. Shrestha; S. Subedi; J. Shrestha Peruvian Journal of Agronomy 4(3): 104–120 (2020) 119 tools for an old science. Bio/Technology, 7(3), 257– 264. https://doi.org/10.1038/nbt0389-257 Tao, C., Hao, W., Ya-dong, Z., Zhen, Z., Qi-yong, Z., Li-hui, Z., Shu, Y., Ling, Z., Xin, Y., Chun-fang, Z., & Cai-lin, W. (2016). Genetic Improvement of Japonica Rice Variety Wuyujing 3 for Stripe Disease Resistance and Eating Quality by Pyramiding Stv-bi and Wx-mq. Rice Science, 23(2), 69–77. https://doi. org/10.1016/j.rsci.2016.02.002 Thomas, W. T. B. (2003). Prospects for molecular breeding of barley. Annals of Applied Biology, 142(1), 1–12. https://doi.org/10.1111/j.1744-7348.2003.tb00223.x Tucker, D. M., Griffey, C. A., Liu, S., & Saghai Maroof, M. A. (2006). Potential for effective marker‐assisted selection of three quantitative trait loci conferring adult plant resistance to powdery mildew in elite wheat breeding populations. Plant Breeding, 125(5), 430–436. https://doi.org/10.1111/j.1439- 0523.2006.01233.x Vuylsteke, M., Peleman, J. D., & van Eijk, M. J. T. (2007). AFLP technology for DNA fingerprinting. Nature Protocols, 2(6), 1387–1398. https://doi.org/10.1038/ nprot.2007.175 Waghmare, S., P Dr, S., Shylaja, M., Mathew, D., Francies, R., Abida, P., & Sivarajan, S. (2018). Analysis of simple sequence repeat (SSR) polymorphism between N22 and Uma rice varieties for marker assisted selection. Electronic Journal of Plant Breeding, 9, 511–517. https://doi.org/10.5958/0975- 928X.2018.00062.5 Walker, D., Boerma, H. R., All, J., & Parrott, W. (2002). Combining cry1Ac with QTL alleles from PI 229358 to improve soybean resistance to lepidopteran pests. Molecular Breeding, 9(1), 43–51. https://doi. org/10.1023/A:1018923925003 Wang, D., Lin, Z., Kai, L. I., Ying, M. A., Wang, L., Yang, Y., YangG, Y., & Zhi, H. (2017). Marker-assisted pyramiding of soybean resistance genes RSC4, RSC8, and RSC14Q to soybean mosaic virus. Journal of Integrative Agriculture, 16(11), 2413–2420. https:// doi.org/10.1016/S2095-3119(17)61682-4 Welsh, J., & McClelland, M. (1991). Genomic fingerprinting using arbitrarily primed PCR and a matrix of pairwise combinations of primers. Nucleic Acids Research, 19(19), 5275–5279. https://doi. org/10.1093/nar/19.19.5275 Wilde, F., Korzun, V., Ebmeyer, E., Geiger, H. H., & Miedaner, T. (2007). Comparison of phenotypic and marker-based selection for Fusarium head blight resistance and DON content in spring wheat. Molecular Breeding, 19(4), 357–370. https://doi. org/10.1007/s11032-006-9067-5 Wilde, F., Schön, C. C., Korzun, V., Ebmeyer, E., Schmolke, M., Hartl, L., & Miedaner, T. (2008). Marker- based introduction of three quantitative-trait loci conferring resistance to Fusarium head blight into an independent elite winter wheat breeding population. Theoretical and Applied Genetics, 117(1), 29–35. https://doi.org/10.1007/s00122-008-0749-8 Willcox, M. C., Khairallah, M. M., Bergvinson, D., Crossa, J., Deutsch, J. A., Edmeades, G. O., Gonzalez‐de‐ Leon, D., Jiang, C., Jewell, D. C., & Mihm, J. A. (2002). Selection for resistance to Southwestern corn borer using marker‐assisted and conventional backcrossing. Crop Science, 42(5), 1516–1528. https://doi.org/10.2135/cropsci2002.1516 Williams, M. N. V, Pande, N., Nair, S., Mohan, M., & Bennett, J. (1991). Restriction fragment length polymorphism analysis of polymerase chain reaction products amplified from mapped loci of rice (Oryza sativa L.) genomic DNA. Theoretical and Applied Genetics, 82(4), 489–498. Xu, J. (2013). Pyramiding of two BPH resistance genes and Stv-b i gene using marker-assisted selection in japonica rice. Crop Breeding and Applied Biotechnology, 13(2), 99–106. https://doi. org/10.1590/S1984-70332013000200001 Yang, R., Yan, Z., Wang, Q., Li, X., & Feng, F. (2018). Marker-assisted backcrossing of lcyE for enhancement of proA in sweet corn. Euphytica, 214(8), 130. https://doi.org/10.1007/s10681-018- 2212-5 Ye, C., Tenorio, F. A., Argayoso, M. A., Laza, M. A., Koh, H.-J., Redoña, E. D., Jagadish, K. S. V, & Gregorio, G. B. (2015). Identifying and confirming quantitative trait loci associated with heat tolerance at flowering stage in different rice populations. BMC Genetics, 16(1), 41. https://doi.org/10.1186/s12863-015-0199- 7 Yu, J., Gu, W. K., Weeden, N. F., & Provvidenti, R. (1996). Development of an ASAP marker for resistance to bean yellow mosaic virus in Pisum sativum. Pisum Genet, 28, 31–32. Yugander, A., Sundaram, R. M., Singh, K., Ladhalakshmi, D., Subba Rao, L. V., Madhav, M. S., Badri, J., Prasad, M. S., & Laha, G. S. (2018). Incorporation of the novel bacterial blight resistance gene Xa38 into the genetic background of elite rice variety Improved Samba Mahsuri. PLoS ONE, 13(5), 1–16. https://doi. org/10.1371/journal.pone.0198260 Zhang, F., Zhuo, D. L., Zhang, F., Huang, L. Y., Wang, W. S., Xu, J. L., Vera Cruz, C., Li, Z. K., & Zhou, Y. L. (2015). Xa39, a novel dominant gene conferring broad-spectrum resistance to Xanthomonas oryzae Marker-assisted selection: a smart biotechnological strategy for modern plant breeding. September - December 2020 120 pv. oryzae in rice. Plant Pathology, 64(3), 568–575. https://doi.org/10.1111/ppa.12283 Zhou, P., Tan, Y., He, Y., Xu, C., & Zhang, Q. (2003). Simultaneous improvement for four quality traits of Zhenshan 97, an elite parent of hybrid rice, by molecular marker-assisted selection. Theoretical and Applied Genetics, 106(2), 326–331. https://doi. org/10.1007/s00122-002-1023-0 Zhou, R., Zhu, Z., Kong, X., Huo, N., Tian, Q., Li, P., Jin, C., Dong, Y., & Jia, J. (2005). Development of wheat near-isogenic lines for powdery mildew resistance. Theoretical and Applied Genetics, 110(4), 640–648. https://doi.org/10.1007/s00122-004-1889-0 Zietkiewicz, E., Rafalski, A., & Labuda, D. (1994). Genome fingerprinting by simple sequence repeat (SSR)- anchored polymerase chain reaction amplification. Genomics, 20(2), 176–183. https://doi.org/10.1006/ geno.1994.1151