Review Article - Journal of Biochemistry and Biotechnology (2021) Volume 4, Issue 6
Molecular markers: A novel vista in vegetable improvement.
Shweta*, Sonia Sood
Department of Vegetable Science & Floriculture, Chaudhary Sarwan Kumar Himachal Pradesh Krishi Vishvavidyalaya, (CSK HPKV) Palampur, India
- Corresponding Author:
- Shweta G
Department of Vegetable Science and Floriculture,
University of CSKHPKV,
Palampur,
India
E-mail: Shwetaguleria228@gmail.com
Accepted date: October 27, 2021
Citation: Shweta, Sood S. Molecular markers: A novel vista in vegetable improvement. 2021; 4(6): 5-17
Abstract
Vegetables are the major source of nutrients in the daily diet in both developing and developed countries. But these groups of plants are most susceptible to a variety of pests. The growth and economic yield are severely reduced under a variety of biotic and abiotic stresses. A number of conventional breeding methods are available for genetic improvement of vegetable crops. But, selection of desirable plants in the breeding programme often becomes misleading due to inadequate biotic and abiotic stress conditions and other environmental factors. Recent advances in the development of molecular markers have made it possible for reliable selection and to speed up the breeding cycle in vegetable crops. Molecular markers directly reveal the polymorphism at the level of DNA. These are tags that can be used to identify specific genes and locate them in relation to other genes. Therefore, in the present article, the authors offered a detailed review of the role of molecular markers to assist breeding programme of important vegetable crops.
Keywords
Molecular markers, Gene tagging, QTL detection, Marker aided selection, Vegetable crops.
Introduction
Conventional plant breeding (classical breeding or traditional breeding) is basically the development of new varieties of plants by using older tools and natural processes [1]. Breeding for improved varieties can no longer rely on ten years cycles and all the technologies to shorten the selection cycles must be mobilized, use of markers is one such technology [2]. Marker is basically a tag which is prominent or helps in the identification of the trait [3]. Markers are classified into four type’s viz., morphological, biochemical, cytological and molecular markers [4]. Morphological markers are visually characterized phenotypic traits like flower colour, seed shape, growth habit and those gene loci that have direct effect on the morphology of plant [5]. These markers enable the assessment of genetic variability and diversity based on single phenotypic difference yet there are limitations associated with these markers and these limitations led to the development of molecular markers [6]. Biochemical markers or isozymes are molecular form of enzyme that is based on the protein staining but having different electrophoretic mobilities. Basically these biochemical markers are encoded by different genes and have same functions [7]. Biochemical markers are allelic variations of enzymes and can be used to estimate the gene frequency, genotypic frequency and successfully help in the detection of genetic diversity, gene flow, structure and subdivision of population [8]. Cytological markers are the variations associated with morphology of chromosomes such as chromosome number, size, sequence specificity, meiotic behavior of chromosome. These are the variations present in the number, size, shape, order, position and banding patterns of chromosomes are called as cytological markers [9]. A cytological marker reveals the differences in the euchromatin and heterochromatin, normal and mutated chromosomes and used in the identification of mapping and linkage groups [10].
A marker is a sequence of DNA which serves as flag post or signpost which is directly or indirectly linked to the trait gene of interest and is generally co-inherited with the trait [ 6].Molecular markers are nucleotide sequences which are estimated by level of polymorphism present between the nucleotide sequences of different individuals. The level of polymorphism is based on insertion, deletion, duplication, translocation and point mutations whereas they did not affect the activity of genes [27]. These markers are basically the landmarks whose position in the genome is known and are directly exposed the polymorphism at DNA level [28]. The ideal molecular marker must have following properties viz., marker should be easily available, inexpensive, non-time consuming, abundant in number, polymorphic in nature, tightly linked to target loci, frequently distributed throughout the genome, preferably <5 centi Morgan (cM) from a gene of interest,indiscriminating, easily reproducible, multiallelic, easy to operate, neutral phenotypically and co-dominant [ 9]. The occurrence of different molecular techniques and different principles and methodologies need cautious deliberation in choosing one or more of such marker types [30]. DNA markers are advantageous and beneficial to use as they are efficiently used in the detection of presence or absence of allelic variation in the genes associated with the trait of interest and tremendously increased the precision and accuracy [31-45]. The theoretical benefits of utilizing DNA markers, the potent value of genetic linkage construction maps and direct selection was first reported about eighty years ago in crop improvement [46]. Now- a-days more efficient molecular markers systems that are inexpensive and involves better detection systems are being developed [47]. Molecular marks were divided into many groups on the basis of mode of their gene action (dominant or co-dominant markers), method of detection (hybridization based molecular markers or PCR based markers) and method of transmission (maternal organelle inheritance, paternal organelle inheritance, biparental nuclear inheritance or maternal nuclear inheritance [48]. Molecular marker were proven to be the most effective and efficient tool in the genetic variation evaluation and in clarification of genetic relationships within and among species [49]. So, the use of molecular genetics or molecular/DNA markers in detecting the DNA differences of single plant has many applications in vegetable crops improvement [50-65]. Various types of molecular markers have been reported till date and discussed in Table 1.
S.No. | Name of marker | Full Form | Reference (s) |
---|---|---|---|
PCR/Hybridization based molecular marker | |||
1 | RFLP | Restriction fragment length polymorphism | Botstein et al., 1980 |
PCR based molecular marker | |||
1. | RAPD | Random amplified polymorphic DNA | Williams et al., 1990 |
2. | AFLP | Amplified fragment length polymorphism | Vos et al., 1995 |
Kumar et al., 2003 | |||
3. | SSR | Simple sequence repeats | Hearne et al., 1992 |
4. | ISSR | Inter simple sequence repeat | Reddy et al., 2002 |
5. | SNP | Single nucleotide polymorphisms | Kumar et al., 2012 |
6. | STS | Sequence tagged site | Fukuoka et al., 1994 |
7. | EST | Expressed sequence tags | Pashley et al., 2006 |
8. | SCAR | Sequence characterized amplified region | Feng et al., 2018 |
9. | CAPS | Cleaved amplified polymorphism sequence | Lyamichev et al., 1993 |
10. | ALP | Amplicon length polymorphism | Ghareyazei et al., 1995 |
11. | SSCP | Single- strand conformation polymorphism | Orita et al., 1989 |
12. | SSLP | Minisatellite simple sequence length polymorphism | Jarmen and Wells, 1989 |
13. | SSLP | Microsatellite simple sequence length | Saghai et al., 1994 |
14. | AP-PCR | Arbitrarily-primed PCR | McClelland and Welsh, 1994 |
15. | AS-PCR | Allele specific PCR | Sarkar et al., 1990 |
16. | DAF | DNA amplification finger printing | Caetano-Anolles et al., 1991 |
17. | SRAP | Sequence-related amplified polymorphism | Robarts and Wolfe et al., 2014 |
18. | DarT | Diversity Array Technologies | Jing et al., 2009 |
19. | Transposon | Retrotransposons | Han, 2010 |
20. | ScoT | Start codon targeted | Zhang et al., 2015 |
21. | DAMD | Direct amplified minisatellite DNA | Somers and Demmon, 2002 |
22. | InDels | Insertion or deletion of bases in the genome | Guo et al., 2019 |
Table 1. Various types of molecular markers.
Literature Review
Advantages and disadvantages of molecular markers
The first big size efforts to produce genetic maps were performed mainly by using RFLP markers, the best known genetic markers at the time [66-75]. Molecular markers are advantageous over morphological and biochemical markers as they have high reproducibility,detect coupling phase of DNA, show co dominant alleles and easily estimate the linked trait to the gene of interest in both hom ozygous and heterozygous individuals [76]. The major disadvantage of utilizing molecular marker is that they are highly expensive, labor intensive, time consuming and requires higher amount of maximum molecular weight DNA [77]. There are several advantages and disadvantages of different types of molecular marker that are discussed in detail (Table 2).
S. No. | Marker | Advantages | Disadvantages | Reference (s) |
---|---|---|---|---|
1. | RFLP | Highly reproducible | Time consuming | Beckmann and Soller, 1986 |
Robust and reliable | Expensive | Tanksley et al., 1989 | ||
Locus specific | High quality of pure DNA needed | Mishra et al., 2014 | ||
Co-dominant | Limited polymorphism | |||
Transferable across the population | Not amenable for automation | |||
No need of prior sequence information | ||||
2. | RAPD | Easy to use | Not locus specific | Demeke et al., 1997 |
Quick and simple | Dominant marker | Jiang, 2013 | ||
Inexpensive | Low reproducibility | |||
Polymorphic | Generally not transferrable | |||
Small quantity of DNA required | Highly purified DNA is required | |||
3. | AFLP | Reliable | Dominant marker | Blears et al., 1998 |
High reproducibility | Complicated methodology | Ridout and Donini, 1999 | ||
Highly polymorphic | High quality and quantity of DNA required | |||
More informative | ||||
Provide good genome coverage | ||||
4. | SSR | Co dominant marker | Developmental cost is high | Provan et al., 2001 |
High reproducibility | Time consuming and laborious | Zane et al., 2002 | ||
Robust and reliable | Polyacrylamide electrophoresis is required | Kalia et al., 2011 | ||
Locus specific | Presence of more null alleles | |||
Transferable across the population | Occurrence of homoplasy | |||
Less quantity of DNA is required | ||||
Amenable for automation and technically simple | ||||
5. | ISSR | Highly polymorphic | Low reproducibility | Dirlewanger et al., 1998 |
Simple and easy to use | Pure DNA is required | Moreno et al., 1998 | ||
No need of prior sequence information | Generally not transferable | Arcade et al., 2000 | ||
Fragment are not same sized | Ng and Tan, 2015 | |||
6. | SNP | Cost effective | Developmental cost is high | Jiang, 2013 |
Co-dominant marker | ||||
High reproducibility | ||||
Widely distributed throughout genome | ||||
No need of prior sequence information | ||||
7. | EST | Co-dominant marker | Marker development is limited to species for which sequencing database already exist | Cato et al., 2001 |
Highly reproducible, robust and reliable | ||||
High degree of sequence conservation | ||||
Enable a transfer of linkage information between species | ||||
8. | SRAP | Simple | Dominant marker | Li et al., 2001 |
Easy to use | Moderate to high throughput ratio | Uzun et al., 2009 | ||
Reliable | ||||
Easy isolation of bands | ||||
9. | DarT | Cost-effective | Dominant marker | Jaccoud et al., 2001 |
High reproducibility | Developmental cost is high | Wenzl et al., 2004 | ||
Highly polymorphic | ||||
High throughput | ||||
Prior sequence information not needed | ||||
10. | Retrotransposons | Simple | Dominant marker | Kalender et al., 1999 |
Easy to use | Kalender et al., 2011 | |||
High reproducibility | Roy et al., 2015 | |||
No need of prior sequence information |
Table 2. Advantages and disadvantages of different molecular markers.
Applications of molecular markers in vegetable crops improvement
There are several applications of molecular markers that aid in improvement of vegetable crops viz., (i) assessment of genetic diversity (ii) gene tagging (iii) DNA fingerprinting for varietal identification (iv) Detection of Quantitative Trait Loci (QTLs) (v) Marker Assisted Selection (MAS) for traits of interest [78-85].
Assessment of genetic diversity: Recent advancements in the field of molecular markers and genome sequencing offer a great and potential opportunity to examine the genetic diversity in a large number of germplasm [86-91]. Molecular markers have been proven as an efficient tool for the assessment of genetic diversity in a very wide range of plant species. This tool is of direct use to plant breeders as it showed the adaption, performance and agronomic qualities of the germplasm [92]. This information gives an idea about the overall genetic range of germplasm of the crops and plant breeders can effectively utilize the germplasm particularly to the unique genes and search aspects [93-105]. Assessment of genetic diversity is very helpful in the study of evolution of plants, their comparative genomics and helps to understand the structure of different populations [106]. Molecular markers now days have been successfully used for the evaluation of genetic diversity and the classification of the genetic material [107]. Many researchers have reported to use molecular markers to assess genetic diversity in various vegetable crops (Table 3).
S.No. | Crop | Molecular marker | Traits improved | Reference (s) |
---|---|---|---|---|
1. | Tomato | RAPD and ISSR | Genetic divergence and high yield of genotypes under high temperature | El-Mansy et al., 2021 |
ISSR | Genetic diversity and genetic variability | Vargas et al., 2020 | ||
SSR and SCAR | Genetic diversity and resistance against fungal diseases | Gonias et al., 2019 | ||
RAPD | Genetic diversity | Herison et al., 2018 | ||
ISSR | Genetic diversity and genetic relationships among varieties | Kiani and Siahchehreh, 2018 | ||
SRAP | Genetic variation and genetic diversity | Shaye et al., 2018 | ||
SSR | Genetic diversity and morphological variation | Kaushal et al., 2017 | ||
SSR | Genetic variation and genetic diversity studies | Benor et al., 2008 | ||
RAPD | Genetic variation | Archak et al., 2002 | ||
RAPD | Genetic diversity | Villand et al., 1998 | ||
2 | Brinjal | SSR | Genetic diversity and population structure | Liu et al., 2018 |
RAPD | Genetic diversity | Sultana et al., 2018 | ||
RAPD | Genetic diversity, molecular characterization and genetic variation | Ansari and Singh, 2013 | ||
RAPD and SSR | Genetic variation and genetic diversity | Verma et al., 2012 | ||
EST-SSR | Genetic diversity and evolutionary relationships analysis | Tumbilen et al., 2011 | ||
RAPD and SSR | Molecular characterization and genetic variation | Demir et al., 2010 | ||
3 | Chilli | SSR | Genetic variability and genetic diversity | Sharmin et al., 2018 |
ISSR | Genetic diversity, level of polymorphism and potential of digital fingerprinting | Thuy et el., 2016 | ||
AFLP | Genetic diversity, genetic studies and identification of chilli genotypes | Krishnamurthy et al., 2015 | ||
SSR | DNA fingerprinting and genetic diversity analysis | Hossain et al., 2014 | ||
RAPD | Genetic diversity and level of polymorphism | Bahurupe et al., 2013 | ||
SSR and SNP | Wide genetic variability and genetic diversity | Yumnam et al., 2012 | ||
RAPD | Genetic diversity | Makari et al., 2009 | ||
4 | Capsicum | SCoT and DAMD | Genetic diversity, genetic structure and estimate of gene flow | Igwe et al., 2019 |
SSR | Pungency characterization, population structure, genetic diversity | Jesus et al., 2019 | ||
Microsatellite and InDel | Genetic diversity and anthracnose resistance | Nugroho et al., 2019 | ||
SSR | Genetic diversity, genetic relationships and population structure improvement | Xiao-min et al., 2016 | ||
5 | Potato | SSR | Genetic diversity and population structure | Lee et al., 2021 |
SSR | Genetic diversity, DNA fingerprinting and molecular variance | La Cruz et al., 2020 | ||
SSR | Genetic diversity and level of polymorphism | Singh et al., 2020 | ||
SSR and RAPD | Genetic diversity, genetic variation, evolutionary relatedness, genetic relationships and molecular characterization | Kapuria et al., 2019 | ||
SSR | Genetic diversity, DNA fingerprinting and detect genetic differences | Tillault and Yevtushenko, 2019 | ||
SSR | Evaluation of genetic diversity and population structure | Wang et al., 2019 | ||
EST-SSR | Genetic diversity and genetic relationships within and among potatoes from different geographical regions | Salimi et al., 2016 | ||
SSR | Genetic diversity, resistance to bacterial wilt, potato virus Y and low chilling temperature | Carputo et al., 2013 | ||
SSR and RAPD | Genetic diversity and cultivar identification | Rocha et al., 2010 | ||
6 | Okra | AFLP | Genetic diversity, genetic variability and level of polymorphism | Massucato et al., 2020 |
AFLP | Genetic and phenotypic diversity | Muhanad et al., 2018 | ||
SSR and RAPD | Genetic diversity and yellow vein mosaic virus resistance | Patel et al., 2018 | ||
SSR | Genetic diversity and genetic variation | Kumar et al., 2016 | ||
SSR | Genetic diversity and genetic relationships among cultivars | Fougat et al., 2015 | ||
AFLP | Genetic diversity and genetic heterogeneity | Kyriakopoulou et al., 2014 | ||
ISSR | Genetic diversity and differentiation | Yuan et al., 2014 | ||
RAPD | Genetic diversity and genetic relatedness | Prakash et al., 2011 | ||
RAPD | Genetic diversity and crop improvement | Sawadogo et al., 2009 |
Table 3. Molecular markers for genetic diversity in different vegetable crops.
Gene tagging: Gene tagging is a pre requisite for Marker Assisted Selection (MAS) and map based cloning in crop improvement programme [108]. Gene tagging refers to the gene mapping of economic value close to wellknown markers. Molecular marker play important role in facilitating the method of traditional gene transfer. Molecular markers that are very closely related to the trait of interest and gene act as tag and these tags are effectively utilized for the indirect selection of genes in breeding programmes [109]. By constructing molecular maps, different genes of economic importance viz., stress tolerance, disease resistance, insect-pests resistance and yield contributing characters have been tagged [110]. Different genes have been tagged to impart resistance in various vegetable crops in resistance by several scientists (Table 4).
S. No. | Crop | Pathogen/Pest | Gene | Marker (s) | Reference (s) |
---|---|---|---|---|---|
1 | Tomato | Yellow leaf curl virus | Ty2 | RFLP | Hanson et al., 2000 |
Tomato mosaic virus | Tm2 | SCAR | Sobir et al., 2000 | ||
Cucumber mosaic virus | Cmr | RFLP | Stamova and Chetalat, 2000 | ||
Verticillium dahliae | Ve | RFLP | Diwan et al., 1999 | ||
Fusarium oxysporum f. sp. Radicislycopersici | Fr2 | RAPD | Fazio et al., 1999 | ||
Cladosporium fulvum | Cf2 | RFLP | Dixon et al., 1995 | ||
Meloidogyne javanica | Mi3 | RAPD | Yaghoobi et al., 1995 | ||
Meloidogyne incognita | Mi | RAPD | Williamson et al., 1994 | ||
2 | Pepper | Tomato spotted wilt virus | Tsw | RAPD | Jahn et al., 2000 |
Tomato spotted wilt virus | Tsw | CAPS | Moury et al., 2000 | ||
Xanthomonas vesicatoria | Bs2 | AFLP | Tai et al., 1999 | ||
3 | Pea | Pea common mosaic virus | Mo | RFLP | Dirlewanger et al., 1994 |
Erysiphe polygone | Er | RAPD | Dirlewanger et al., 1994 | ||
4 | Bean | Common bean mosaic virus | I | RAPD | Meiotto et al., 1996 |
5 | Cucumber | Fusarium oxysporum f. sp. Melonis | Fo | SSP | Wechter et al., 1998 |
m2 | |||||
6 | Melon | Fusarium oxysporum f. sp. Melonis | Fo | RAPD | Wechter et al., 1995 |
m2 |
Table 4. Molecular markers linked to major resistant genes in different vegetables.
DNA fingerprinting for varietal identification: It is one of the most important aspects that identifies and detect any genotype of crops along with whole living organisms [111]. DNA fingerprinting can successfully utilize for varietal identification as well as for detecting variability in a wide variety of germplasm [112]. Although any type of marker can be used for DNA fingerprinting but RAPDs, microsatellite and RFLPs are the markers of preference for the purpose because all these markers are PCR based and did not require any pre information on nucleotide sequences [113-141]. Identification of different varieties of vegetable crops has been reported by several workers (Table 5).
S.No. | Vegetable crop (s) | Molecular marker (s) | Reference (s) |
---|---|---|---|
1 | Tomato | Microsatellites, RAPD, RFLP | Kaemmer et al., 1995 |
Bredemeijer et al., 1998 | |||
Noli et al., 1999 | |||
2 | Brinjal | RAPD | Karihaloo et al., 1995 |
3 | Chilli | RAPD, ISSR | Mongkolporn et al., 2004 |
4 | Pepper | RAPD, AFLP | Prince et al., 1995 |
Paran et el., 1998 | |||
5 | Potato | RAPD, AFLP, ISSR, Microsatellites | McGregor et al., 2000 |
Ashkenazi et al., 2001 | |||
6 | Pea | RAPD | Thakur et al., 2018 |
7 | Beans | RAPD, RFLP | Stockton and Gepts, 1994 |
8 | Onion, garlic and related species | AFLP, Microsatellites, ISSR, RAPD | Arifin et al., 2000 |
Fischer and Bachmann, 2000 | |||
9 | Brassica | RAPD, Microsatellites | Margale et al., 1995 |
Cansian and Echeverrigaray, 2000 | |||
10 | Cucurbits | RAPD, ISSR, Microsatellites | Gwanama et al., 2000 |
Danin et al., 2001 | |||
11 | Carrot | RAPD, AFLP | Shim and Jorgensen, 2000 |
12 | Sweet potato | RAPD, AFLP | He et al., 1995 |
13 | Lettuce | AFLP, Microsatellites | Hill et al., 1996 |
14 | Asparagus | RAPD | Khandka et al., 1996 |
Roose and Stone, 1996 | |||
15 | Spinach | Microsatellites | Groben and Wricke, 1998 |
16 | Artichoke | RAPD | Tivang et al., 1996 |
Table 5. Identification of varieties of different vegetables by using molecular markers.
Detection of QTLs: The identification and detection of linkage between QTLs and markers are the prime and foremost objective of the breeders that are engaged in the resistance breeding of plants though it can be performed using various statistical methods [143].Disease resistance can be detect with ordinary scales whether data do not always show normal distribution, so researchers have been testing putative QTLs with non-parametric statistical tests and procedures [144].The conclusion of genetic studies of complex interactions has been observed and first time reported the insect resistance in tomato [145].In addition to this, QTL mapping could be useful for identify and detect the loci associated with quantitative components of resistance to infections in crop plants, its rate of multiplication as well as its movement and in the host and progression of the disease [146].By this unique technique of detection of QTL new genes for partial resistance might be identified and utilized for resistance in crop plants [147]. Different types of QTLs have been detected by several researchers in vegetable crops (Table 6).
S.No. | Crops | Traits | QTL/gene | Chromosome number | Marker | Population used | Source | Reference (s) |
---|---|---|---|---|---|---|---|---|
1 | Tomato | Fruit morphology | QTL | 10 | SNP | RIL | NC30PXNC-22L-1 | Adhikari et al., 2020 |
Late blight and yield | QTL | 11 | SNP | F2 | Koralik | Brekketet et al. 2019 | ||
Glandular trichomes | QTL | 1 | SNP | BC | Solanum habrocha-ites | Bennewitz et al. 2018 | ||
Late blight | QTL | 2,3,10 | SNP | F2 | PI163245 | Ohlson et al. 2018 | ||
Early flowering | QTL | 1 | SNP | F2 | BoneMM cultivar | Ruanggrak et al. 2018 | ||
Fruit mineral content | QTL | - | SSR | RIL | Solanum pimpinellifolium | Capel et al., 2017 | ||
Late blight | QTL | 9 and 12 | SNP | F2 | L3707 | Panthee et al., 2017 | ||
2 | Cucumber | Salt tolerance | QTL | 6 | SSR | RIL | CG104 and CG37 | Liu et al., 2021 |
Fruit size and fruit shape | QTL | 1 and 6 | SNP | F2 and BC1F1 | Inbred line CNS21 and Inbred line RNS7 | Gao et al., 2020 | ||
Low temperature | qLTG1.2 | 1 | - | RIL | Low germination tolerant variety | Yagcioglu et al. 2019 | ||
Germination ability | qLTG2.1 | 2 | - | RIL | Low germination tolerant variety | Yagcioglu et al. 2019 | ||
Cucumber mosaic virus | CMV6.1 | 6 | SSR | RIL | Inbred line 02245 | Shi et al., 2018 | ||
Alternaria leaf spot | Ps15.1, ps15.2 | 5 | SSR | RIL | GY14 | Slomnicka et al. 2018 | ||
Fruit peduncle length | Qfp16.1 | 6 | SSR | F2 | Inbred line 1101 | Song et al. 2016 | ||
Powdery mildew | Pm1.1, pm1.2 | 1 | SSR | F2.3 | WI 2757 | He et al., 2013 |
Table 6. Detection of QTLs in different vegetable crops.
Marker assisted selection: Marker assisted selection refers to the use of molecular (DNA) markers to assist phenotypic selection in crop improvement [40]. Basically, it is a technique in which phenotypic selection is made on the basis of genotype of a marker [148].It is based on the concept that it is possible to infer presence of a gene from the presence of a marker which is tightly linked to the trait of interest [149]. MAS provided a tremendous potential for increasing the selection efficiency by allowing for earlier selection and reducing plant population size used during selection [150]. It is a molecular breeding technique which helps to avoid the difficulties related to traditional plant breeding and it has tremendously changed the standardof selection[151-152].Plant breeders mostly use MAS for the identification and detection of suitable dominant or recessive allele across the generation and for the identification of most favourable individuals across the segregating progeny [153]. There are four important schemes in marker assisted selection namely marker- assisted backcrossing, gene pyramiding, marker-assisted recurrent selection, genome selection in crop plants [154]. Marker-assisted selection for the traits of interest has been reported in different vegetable crops by several scientists [155-159] (Table 7).
S.No. | Crop | Marker/gene | Lines used | Trait improved | Reference (s) |
---|---|---|---|---|---|
1 | Cabbage | InDel markers A1 and M10 | D21, D29, D70, D120 and D162 | Head splitting and Fusarium wilt resistance | Li et al., 2020 |
2 | Tomato | TG101 (RFLP) and Fr1 gene | Pusa Ruby | Fusarium wilt resistance | Devran et al., 2018 |
SNP and Bwr-6 and Bwr-12 | Pusa Rohini, Pusa 120 | Bacterial wilt resistance | Kim et al., 2018 | ||
ACY (InDel) and Ty-3 gene | Pusa Rohini, Pusa 120 | Yellow leaf curl virus resistance | Nevame et al., 2018 | ||
3 | Onion | Orf725 | A and B lines of onion in Brazilian germplasm | Cytoplasmic male sterility | Ferreira and Santos, 2018 |
4 | Cucumber | SSR11 | Cmv6.1 | Cucumber mosaic virus resistance | Shi et al., 2018 |
pmsSR27 pmSSR17 | Pm-s | Powdery mildew resistance | Liu et al., 2017 | ||
5 | Watermelon | MCPI11, CYSTSIN and Pm gene | Arka Manik | Powdery mildew resistance | Gama et al., 2015 |
6 | Pea | SCAR and er-2 gene | JI2480 | Powdery mildew resistance | Katoch et al., 2010 |
Table 7. Marker assisted selection in different vegetable crops.
Discussion and Conclusion
Genetic diversity means the variety of genes in all organisms from human beings to crops, fungi, bacteria and viruses. It determines the distinctiveness of each individual or population within the species. There are basically four methods of measuring genetic diversity namely ethinobotanical classification, morphological, biochemical and molecular characterization. Morphological markers allow the finding of genetic variation based on Individual phenotypic variations. However, there are limitations confined to these types of markers. Morphological markers limitations lead to the assessment of biodiversity from relying on morphological markers to using isozymes and DNA markers that is popularly known as molecular markers. There are various types of molecular markers which are classified based on variation type at the DNA level, mode of gene action and method of analysis. They are key tools in genome analysis which ranges from localization of a gene to improvement of plant varieties through marker aided selection. Even though there are various uses of DNA markers but among all Marker Assisted Selection (MAS) is the most promising technique for crops cultivar development. MAS can be employed as an effective tool to facilitate selection of progeny in an early generation who have desirable traits resulting speeding up of the selection procedure in the breeding programme. There are different conventional and modern breeding tools and techniques that can be utilized for crop improvement of vegetable crops despite the ban on genetically modified organisms. The controlled crosses between individuals produce desirable genetic variation to be recombined and transferred to next progeny through natural process.
The last thirty years have witnessed a continuous and tremendous development I the molecular markers technology from RFLP to SNPs and a diversity of arraytechnology- based markers. In spite of the presence of these highly advanced molecular genetic techniques, we are still not achieving our goals. Unfortunately, molecular markers are currently unavailable for several important traits controlled by many genes or polygenes. The main reason behind these lies in inaccurate phenotyping. High-throughput phenotyping techniques solve these problems by using light, cameras, sensors, computers and highly modi?ed devices for the collection of very precise phenotypic data, which is a core requirement to achieving our breeding goals successfully. The coming years are likely to see continued innovations in molecular marker technology to make it more precise, productive and costeffective in order to investigate the underlying biology of various traits of interest.
Disclosure Statement
No potential conflict of interest was reported by the authors.
References
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