Research Article

Insight in the utilization of Marker Assisted Selection in Cotton (A Review)  

Yuksel Bolek1 , Khezir Hayat1 , Adem Bardak1 , MuhammadTehseen Azhar2
1. Department of Agricultural Biotechnology, Faculty of Agriculture, Kahramanmaras Sutcu Imam University, Kahramanmaras, Turkey
2. Department of Plant Breeding and Genetics University of Agriculture, Faisalabad, Pakistan
Author    Correspondence author
Molecular Plant Breeding, 2016, Vol. 7, No. 10   doi: 10.5376/mpb.2016.07.0010
Received: 26 Nov., 2015    Accepted: 27 Nov., 2015    Published: 30 Mar., 2016
© 2016 BioPublisher Publishing Platform
Preferred citation for this article:

Bolek Y., Hayat K., Bardak A., and Azhar M.T., 2016, Insight in the utilization of Marker Assisted Selection in Cotton (A Review), Molecular Plant Breeding, 7(10):1-17


Upland cotton represents the most important, and natural fiber crop in the world. Limitations in conventional breeding program for genetic improvement is due to the lack of knowledge about yield productivity and fiber quality traits. The use of molecular markers for the detection and exploitation of DNA polymorphism is one of the significant developments in the field of molecular genetics. The availability of reference genome of G. raimondii L., G. arboreum L., and next generation sequencing, routed it on the fast track for exploring the variability among genotypes of cotton. There is no molecular marker available which can fulfill all the requirements of cotton scientists. Plant breeders should utilize genomics in the breeding programs for effective selection of potential parents for certain traits. The genomic research work could use quantitative trait loci mapping, genome wide associations and next generation sequencing strategies. This review highlights the recent developments of various molecular markers for analyzing genetic diversity, constructing linkage maps and genomics tools which will assist in marker assisted selection in cotton.

Cotton; Genome; Genetic diversity; DNA marker; SSR; SNP; GBS; MAS; GWAS

1 Abbreviations
RFLP (Restriction fragment length polymorphism), AFLP (Amplified fragment length polymorphism), RAPD (Random amplified polymorphic DNA), ISSR (Inter simple sequence repeat), SCAR (Sequence characterized amplified regions), SSR (Simple sequence repeat), STS (Sequence tag sites), ESTs (Express sequence tags), CAPS (Cleavage amplified polymorphic site), SNP (Single nucleotide polymorphism), GBS (Genotyping by sequencing), MAS (marker assisted selection), GWAS (Genome wide association studies)

2 Introduction
Cotton (Gossypium spp.) being the world most widely sown fiber crop, has an important share in global economy (Cuming et al., 2015) and being a significant contributor of oilseed with an approximate utilization of about 115 million bales (Waqas et al., 2014). Cotton is cultivated by more than 80 countries in the world (Sunilkumar et al., 2006; Abdurakhmonov et al., 2012) on 32-34 million hectares (2010/11 to 2012/2013) with annual total production of 25.65 million metric tons (MT) (forecast for 2013/14, USDA report, 2013). Wendel et al., (2009); Grover et al. (2014) has described 52 different Gossypium species including 7 tetraploid (AD) and 45 diploid differentiated into eight genomes (A-G and K). Moreover, allotetraploid Gossypium hirsutum L. (2n=4x=52) is the most prominent, which accounts for over 95% of the world crop while G. arboreum and G. herbaceum together share 2% cotton on global level (Zhang et al., 2008).

Molecular marker is a specific DNA portion with a known position on the chromosome (Kumar, 1999), or a gene whose phenotypic expression is frequently easily distinguished and used to detect an individual (King and Stansfield, 1990; Schulmann, 2007). Genetic markers are divided into three groups: (1) morphological markers which themselves have phenotypic characters; (2) biochemical markers, having allelic variants of enzymes called isozymes; and (3) DNA markers, which show sites of variation in DNA (Joshi and Nguyen 1993; Winter and Kahl, 1995; Jones et al., 1997; Gupta et al., 1999). DNA markers are having the property of polymorphism which is based on the differentiation of homozygotes and heterozygotes (Roychowdhury et al., 2014). Molecular markers are more authentic for fertility restoration than morphological markers in several lines of cotton (Shanti et al., 2001); DNA markers having high polymorphism in germplasm collections are desired in marker assisted selection (Bolek, 2003).

Marker assisted selection has advantage over conventional breeding, reviewed by many researchers (Collard and Mackill, 2008; Kumpatla et al., 2012; Waqas et al., 2014). Plant breeders utilize DNA markers for selection of desirable traits on molecular basis in spite of observing phenotypically (Helentjaris et al., 1986), furnishing the basis for using the molecular assisted selection (Welsh and McClelland 1990; Vos et al.,1995; Struss and Plieske, 1998). Molecular markers are desired for improving traits in many essential crops; rice (Mackill et al., 1999), wheat (Koebner and Summers, 2003), maize (Stuber et al., 1999; Tuberosa et al., 2003) and barley (Thomas, 2003; Williams, 2003). Cotton is an important cash crop at global level and marker assisted selection has not got desired goals due to compatible barriers through historic domestication and insufficient polymorphism (Iqbal et al., 2001; Rahman et al., 2005; Abdurakhmonov et al., 2008).

Many economical traits such as yield, quality and some forms of disease resistance are controlled by many genes and are known as quantitative traits (also ‘polygenic, or ‘complex’ traits). In order to increase the production; awareness about the extent of heredity about economical traits on molecular basis has shifted plant breeders to marker assisted selection (Bolek et al., 2005). DNA markers linked to the QTL of interest increase the efficiency of breeding, decreasing costly and lengthy phenotypic selection (Collard et al., 2005). Transference of required economic valuable characters from wild species to upland cotton having minimum linkage drag is accomplished by marker assisted selection which is based on tracing of genomic regions in interspecific programs by molecular markers and quantitative trait loci (Tanksley et al., 1989; Young and Tanksley, 1989; Abdurakhmonov et al., 2011). Through the increased numbers of next generation sequencing, enormous markers can be analyzed across the genomes which allows genome-wide studies (Schuster, 2011).

For genetic improvement with the objective of enhancing yield of field crops, it is necessary to learn about molecular markers evolution and their utilization in crop improvement. The objective of this review is to describe the utilization and evolution of molecular marker technologies and overview MAS activities in cotton.

3 DNA Makers in Cotton
DNA profiling in plants is principally used for observing genetic diversity, germplasm maintenance and determining markers affiliated with required traits. Genetic conservation is based on grip about extent of genetic diversity prevailing in the germplasm (Jubrael et al., 2005). Molecular markers are easy to evolve due to presence of enormous genomic databases (Andersen and Lubberstedt, 2003) and they are highly useful for plant breeders as these markers are source of isolation, maintenance, detection of heredity, marker assisted selection and genomic profiling (Kalia, 2011). Mishra et al., (2014) suggested that the ideal DNA marker should be having the following traits;

1. Highly polymorphic as it is compulsory for genetic studies,
2. Co-dominance which shows the difference of homozygotes and heterozygotes of diploid organism,
3. Frequent occurrence in the genome,
4. Selective neutral behavior,
5. Cheap and fast assay,
6. Reproducible and easy exchange of data among laboratories.

The development of molecular markers is based on cost of identification of marker methodology, efficiency and polymorphism (Bernardo, 2008). The classification of DNA markers into three classes is based on the method of their detection: (1) hybridization-based; (2) polymerase chain reaction (PCR) based and (3) DNA sequence based (Winter and Kahl, 1995).


4 Restriction Fragment Length Polymorphism (RFLP)
RFLP is the primarily known type of hybridization-based molecular marker in plant genome and initially used during 1975 for the detection of DNA sequence polymorphism in gene mapping (Helentjaris et al., 1986). The methodology of RFLP depends on restriction enzymes which show comparison among DNA sequences individually. Dissimilarity in DNA sequences produce loss, gain or alteration of restriction site. Therefore, digestion of DNA with restriction enzymes produce fragments having difference in number and size between populations and species. RFLP study is an abundantly authentic technique for DNA profiling and for computing heredity. Many scientists produced genome mapping of cotton by using RFLPs (Ulloa and Meredith, 2000). First molecular map of the cotton genome was established by utilizing 705 RFLP loci and partitioned into 41 linkage groups (Reinsich et al., 1994). The efficacy of RFLP markers in marker assisted selection (MAS) was described and RFLP resistance allele for bacterial blight resistance germplasm was confirmed (Wright et al., 1998). In the science of omics, RFLPs have played a significant part (Rahman et al., 2009). As RFLP technique includes costly chemicals and takes long time for analysis which limits its use in marker assisted selection (Agarwal et al., 2008).

5 AFLP (Amplified Fragment Length Polymorphism)
AFLP approach collaborate RFLP with the adoptability of PCR-based technology by ligating adaptors to the restricted DNA (Lynch and Walsh, 1998). The focal point of AFLP is its ability for “genome representation” evaluate the representative DNA regions dispersed throughout the genome at the same time. In plants AFLP markers can be produced and there is no need for prior information and sequence analysis for development of primer. For genetic mapping, AFLP is helpful owing to their high availability and randomly distribution all over the genome (Vos et al, 1995). A linkage map of cotton was published using the AFLP and RAPD markers (Altaf et al., 1997). Phylogenetic studies have been done by using AFLP to observe the genetic resemblance (Abdalla et al., 2001; Lacape et al., 2003) and map saturation in cotton (Zhanget al., 2005). The benefits of AFLP include: 1) Reliable and reproducible (Jones et al., 1997). 2) No need of DNA sequence for analysis 3) It is information-rich due to having ability for analyzing a large number of polymorphic loci simultaneously with a single primer combination on a single gel as compared to RFLPs and microsatellites (Russell et al., 1997). Both good quality and partially degraded DNA can be used for digestion but the DNA should be free of restriction enzyme and PCR inhibitors.

6 Randomly Amplified Polymorphic DNA (RAPD)
Random nucleotide sequence magnification of genomic DNA having one primer is established by using RAPDs (Williams et al., 1990). DNA fragments having sequence of about 10 bp are amplified with artificial primers by using PCR (Khanam et al., 2012). RAPDs are used for genotype profiling by using primers which shows polymorphism about precise information of sequence. The primers used for this technique should be free from palindromic sequences and should have minimum 40% GC contents in the fragments (William et al., 1990). The methodology of RAPD has been studied by a number of researchers in cotton (Khan et al., 2000; Rahman et al., 2002; Hussein et al., 2005). Sheidail et al., (2007) conducted phylogenetic studies in cotton and argued that this procedure is helpful for introgression of desirable traits. RAPDs were used in cotton for comparing cotton cultivars resistance to jassids, mites and aphids (Geng et al., 1995). In addition, linkage maps established and genetic diversity was observed by using RAPD in cotton (Lu and Mayers, 2002). DNA finger printing, mapping and genetic diversity has been observed in cotton through RAPDs (Zhang et al., 2008; Zahra et al., 2011). The demerit of this methodology is that in order to obtain highly polymorphic bands rigorously follow the reaction conditions but practically band profiles are hard to magnify.

7 Inter-Simple Sequence Repeat (ISSR)
DNA fragments which are amplified from an amplifiable location between two similar simple sequence, repeated sequences are located at adjacent points are called ISSR (Sharma et al., 2012). Among simple sequence repeat polymorphism is observed using primer (16-25bp) adjacent to a single SSR and annealing occur at either ends (Sharma et al., 2012). ISSR marker methodology establishes the comprehensive use of RAPDs amalgamating the merits of AFLPs and SSRs (Bornet and Branchrd, 2001). Usually ISSR primers have substantial fragments contrary to RAPD primers, enabling elevated annealing temperature which produces high polymorphic bands converse to RAPDs (Reddy et al., 2002). All over the globe the scientists are using ISSR markers vastly in cotton improvement, phylogenetic study and for mapping (Bornet et al., 2002; Sica et al., 2005). ISSR provides easy way for examining the polymorphic bands conversely to other molecular markers (Dongre et al., 2007). Noorulhamdi et al., (2013) observed genetic diversity and studied agronomic traits in Gossypium hirsutum and F2 progenies by using ISSR.

8 Sequence Characterized Amplified Region (SCAR)
A technique in which DNA sequence is detected by using polymerase chain based marker having well defined pair of oligonucleotide primers (Paran and Michelmore, 1993). SCARs are advantageous over RAPDs having capability to recognize merely a single locus, the PCR reaction conditions are less manifested during amplification and mostly transformed into co-dominant markers (Paran and Michelmore, 1993). These markers are more beneficial for genome mapping being co-dominant contrary to dominant RAPDs and are having the ability to evaluate pooled genomic libraries through PCR for map based cloning. The methodology of sequence characterized amplified region is prominent among the researchers for mapping studies within closely related species (Michelmore et al., 1991; Tanaka et al., 2006). SCAR markers have been used for disease and insect resistance and also utilized for restoration of fertility in crops (Nair., 1995; Norio, 1997; Liu., 1999). SCAR marker is cost effective and highly polymorphic which makes it suitable to be used for evaluating large numbers of mapping population in cotton (Guo et al., 2003).

9 Sequence Tagged Site (STS)
Sequence-tagged site (STS) are the markers which utilize polymerase chain reaction with particular primer that produces a marker linked to desired character (Feng et al., 2005). Sequence tag site is manifested by a pair of oligonucleotides that are developed by sequencing an RFLP probe representing a mapped low copy number sequence (Blake et al., 1996). STS markers are simple to use, highly polymorphic, co-dominant and suitable for high throughput sequencing (Remon and Jung, 2000). Breeders use STS markers for developing restorer parental lines for hybrid cotton (Feng et al., 2005).

10 SSR (Simple Sequence Repeat) (Microsatellites)
Short tandem repeats are polymorphic bands found in DNA that contain 1-6 bp repeating units (Bidichandani, et al., 1998). Especially if the tandem repeats are higher than 10, then this marker shows high level of inter and intra-specific polymporhism (Queller et al., 1993). Repetitive sequences are found all over the genomes and chain of mono, di and tri nucleotides repeats are known as microsatellites. These markers are multiallelic, co-dominant, intensively changing and are distributed randomly all over the genome. During polymerase chain reaction precise flanking fragments serve as primers that are utilized for the amplification of simple sequence repeats for observation. During replication tandem repeats produce simple sequence repeats due to copy choice recombination (Viguera et al., 2001) or dissimilarity occur in the specific nucleotide sequence due to unbalance crossing over (Yu and Kohel, 1999). Simple sequence repeats play important role in germplasm characterization, screening of varieties, pedigree analysis and genome mapping (Billotte et al., 1999). SSR markers are the desired type of markers in cotton as having higher possibility for phylogenetic study (Zhang et al., 2008). SSR markers and their mapping information can be found in substantial Cotton Gene database ( markers). SSR analysis needs small quantity of DNA, not having precise quality and the inferences are discussed; SSRs are employed in plant breeding, conservation biology and as forensics in population genetics, genetic diversity analysis and genetic mapping (Coetes and Byrne, 2005). For assisting the development of saturated and fully integrated saturated genetic map of cotton “The International Cotton Genome Initiative” was launched that will furnish the way for the evolvement of a consensus map (Yu et al., 2005).

Simple sequence repeats have been utilized for analyzing genetic diversity in cotton and closely related species (Rungis et al., 2005; Liu et al., 2006), significant hindrance for use in cotton breeding due to limitation of genetic variability (Iqbal et al., 2001; Liu et al., 2006). Many researchers have used SSRs for refinement of fiber traits (Ulloa et al., 2002; Zhang et al., 2003; Lin et al., 2005; Frelichowski et al., 2006; Zhang et al., 2013). Several genes for disease resistance have been observed in cotton through applying SSR markers; including root knot nematode [Meloidogyne incognita (Kofoid and White)] (Ynturi et al., 2006), verticillium wilt (Verticillium dahliae Kleb.) (Bolek et al., 2005), bacterial blight [Xanthomonas axonopodis pv. malvacearum] (Rungis., 2002; Xiao., 2010); cotton leaf curl virus (Aslam et al., 1999) have been tagged by SSR molecular markers. Commonly the null-alleles are found which are not polymorphic, diverse microsatellites are examined to overcome null alleles using population studies having enormous SSR primers (Weising et al., 2005). Association mapping performed in Chinese cotton germplasm and QTLs for seed cotton yield and fiber quality observed by using SSRs which will provide good parents for developing good cultivars (Zhang et al., 2013). Qin et al., (2015) employed SSR markers used for the association mapping of 241 Upland cotton collections, results provide new useful markers for marker-assisted selection in breeding programs and new insights for understanding the genetic basis of upland cotton yields and fiber quality traits at the whole-genome level. Species specific SSRs are generally employed for introgression, but with extending genetic distance the extent of loci that successfully amplify may be reduced. 


11 Expressed Sequence Tags (EST-SSRs)
Transcribed regions of the DNA (EST- SSRs) are mostly maintained throughout the species compared to genomic SSRs from the untranslated regions (Cuadrado and Schwarzacher, 1998), and are having more substitution to genomic SSRs. The evolution of enormous expressed sequence tags produces a valuable origin of PCR-based markers for targeting SSRs. Among divergent species in plants about 1-5% of the expressed sequence tags have tandem repeats having acceptable length for the development of markers (Kantety et al., 2002). During gene expression EST-SSRs have more chances of being functionally linked with variations than genomic SSRs (Gao et al, 2004). Different genome analysis techniques provide increased quantity of ESTs which facilitated in the recognition of SSRs domains from the ESTs. Moreover, many attempts done for the development of EST-SSRs in cotton (Qureshi et al., 2004); for phylogenetic analysis (Arunita et al., 2010) and genomic map construction (Guo et al., 2007; Lin et al., 2009). Genic SSRs have some intrinsic advantages over genomic SSRs because they are quickly obtained by electronic sorting, and are present in expressed regions of the genome (Varshney et al., 2005). However, EST-SSRs exhibit low level of polymorphism than conventional SSRs. Wang et al., (2015) utilized EST-SSRs for developing genetic linkage map in cotton, and observed that marker development was very useful for the saturation of the allotetraploid genetic linkage map, genome evolution studies and comparative genome mapping.

12 Cleaved Amplified Polymorphic Sequence (CAPs)
The integration of RFLP and PCR (Semgan et al., 2006b) through which DNA particles are amplified using PCR, followed by restriction enzyme digestion is accomplished by CAPs. Cleaved amplified polymorphic sequences derive polymorphic markers from monomorphic markers which are mostly co-dominantly transferred (Karaca and Gul, 2011) and show high polymorphism among closely related accessions. CAPs primers developed from ESTs are more useful as genetic markers for comparative mapping study than those markers derived from non-functional sequences such as genomic microsatellite markers (Matsumoto and Tsumura, 2004). These markers are helpful for evolving patents in cotton and applicable in characterization of germplasm, genetic diversity analysis for utilization in breeding programs and genome mapping (Karaca and Gul, 2011).

13 Single Nucleotide Polymorphism (SNP)
Precise and elucidated location at chromosome having fragment of DNA among two accessions demarcated by a single base is called single nucleotide polymorphism; due to mutation either transition or transversion and deletion or insertion abnormality (Ayeh, 2008; Hearne et al., 2008). SNPs are highly secured markers as furnish phenotype directly (Batley and Edwards, 2007). They are the easiest type of markers as having minor heredity entity as alone base and can produce large number of markers. SNPs are frequently found in plants and animals (Xiao et al., 2010). SNPs are co-dominant, normally assigned and connected with morphological changes as used as a marker (Lindbeld et al., 2000). Now a day’s researchers all over the world have thirst for single nucleotide markers for many species as SNP-based markers overcome other markers, owing to the enormous persistent polymorphism in the genome, both within and between (Berard et al., 2009). Quick detection of SNPs is based on sequence information in EST libraries (Bundock et al., 2006) or on the basis of primer design for re-sequencing (Choi et al., 2007) in species having no available genome sequence. Universally well-known method for SNP discovery is mass spectrometry and sequenom (San Diego, USA), evolved an efficient genotyping technique (Buetow et al., 1999); moreover, SNPs can be identified by SNP flow software (Weissensteiner et al., 2013).

SNPs have been detected in many species including model species such as Arabidopsis thaliana (Jander et al., 2002), many field crops like maize (Ching et al., 2002), wheat (Ablet et al., 2006) and in humans (Sachidanandam et al., 2001). SNPs furnish fast and efficient genotyping of enormous population by using next generation sequencing methodology.

SNPs have been identified in cotton by scientists all over the world for analyzing genetic diversity, phylogenetic analysis and genetic mapping in the Gossypium genome (Deynze et al., 2009). SNPs among two accessions of Gossypium arboreum were examined between 30 conserved regions of expressed sequence tags by Shaheen et al., (2010), and identified as a whole 27 SNPs consisting of six indels and 21 substitutions in 7804 bp having a frequency of one SNP/371 bp and one indel after every 1300 bp; 52% transitions and 48% SNPs were transversions in the observed SNPs. Affymetrix has developed “Gene Chip” for cotton genome array consisting of 239777 probe sets containing 21485 cotton transcripts which is in verification stage and then will be available commonly. For SNP development the sequences are collected from Genbank, dbEST and RefSeq supplied by partners all over the world. Roche 454 pyrosequencing technique in allotetraploid cotton produced more number of SNPs through reduced representation library sequencing (Byers et al., 2012). Desirable SNPs were observed by using conservative approach; KASPar assay was about 35.8% for conversion of SNPs. Genome map of 1688 cM was developed in G. hirsutum using 367 SNP markers. Wang et al., (2013) developed linkage map by using SNPs and QTLs were analyzed. A total of 15.971 markers, including gSSRs, EST-SSRs, SRAPs, and SSCP-SNPs. Gore et al., (2014) produced a linkage map and conducted a quantitative trait locus (QTL) analysis of 10 agronomic and fiber quality traits in a recombinant inbred mapping population and observed QTLs in introgressed population by using SNPs. Hulse-Kemp et al., (2015) has developed inter- and intra-specific maps in cotton by using CottonSNP63K, the most saturated map for cotton to-date. The array and maps provide a foundation for the genetic dissection of agronomically and economically important traits, and crop improvement through genomics-assisted selection. It will also foster positional cloning and genome assembly efforts. The fast growing contribution of portable markers in cotton furnishes inexpensive way for gene isolation and linkage mapping for breeding cotton to obtain desirable objectives.

14 Genotyping by Sequencing, GBS
For next generation sequencing multiplex libraries are prepared by utilizing restriction endonuclease for detecting a minute section of the genome coupled with DNA barcoded adaptors through genotyping by sequencing (GBS). This technique has manifested to be fast among the number of species and having ability of evolving enormous markers (Elshire et al., 2011; Poland et al., 2012a). Ultimate goal of functional genomics is to screen better plant types in crop improvement by sharing phenotypic information from phenotype to genotype. Genotyping by sequencing, will evolve first to capture more sequence variants and then to whole-genome resequencing (Poland and Trever, 2012). GBS technique has been modified right from start including restriction association DNA which utilizes restriction enzymes for targeted reduction of genome complexity integrated with next generation sequencing (Baird et al., 2008). The improved form of RAD; utilizes restriction enzymes that cut upstream and downstream of target site (Wang et al., 2012) which allows marker intensity adjustment by producing same length tags permitting about all the restriction sites to be analyzed. Genotyping by sequencing having a diverse capability that can produce numerous SNPs in research and appropriate for gene pool maintenance, diversity analysis, genomic selection, gene mapping and other plant improvement methodologies (Elshire et al., 2011). GBS furnishes cost effective way for studying populations, helps in association mapping by which genomic selection can be carried on large scale (Poland and Trevor, 2012). This methodology has been used in number of species of cotton (Gossypium hirsutum L.), sorghum (Sorghum bicolor), following basic protocol (Poland et al., 2012) with minor changes. Gore et al., (2014) developed genetic map in cotton having 841 SSR and SNP loci contributing to half of the tetraploid cotton genome through execution of GBS together with fluorescent-based SSR genotyping. GBS application is highly interweaved in cultivated cottons due complicated allotetraploid genetic constitution and having repetitive DNA (Li et al., 2014).

15 Genome Wide Association (GWAS)
Exploration of genetic diversity available in germplasm, genetic map construction and QTL mapping for economic and agronomic traits has been conducted by utilizing segregating populations through DNA marker techniques (Chen et al., 2007; Zhang et al., 2008) which are essential for fastening marker assisted selection. It is challenging for bi-parental population to detect closely linked markers for molecular breeding due to confined crossing over. Moreover, the density of polymorphism in bi-parental population is restricted as some minor QTLs are not detected.

There is a substitute methodology for QTL mapping that is called “association mapping” which relies on linkage disequilibrium and utilizes cultivars having distinctive traits (Zhao et al., 2014). Association mapping relies on the association of alleles among marker locus and phenotypic locus. This technique can be induced by mutation, genetic drift, population selection etc and particularly in plants that the extent of inbreeding caused by hybridization (Hart and Clark, 1997). Hereditary basis of the characters permitting exclusive selection of parents and allowing successors for mutagenesis and transgenics through genome wide association (GWAS). This technique elicits many obstacles of traditional genetic mapping due to furnishing increased resolution generally to the locus and utilizing highly examined populations having genetic variation associated with phenotypic variation. This technique relies upon linkage disequilibrium among the loci. It is compulsory in LD mapping to characterize LD magnitude and pattern in population under observation for acquisition of desired objectives. Magnitude of relation, extent of parental recombination and linkage disequilibrium in gene pool permits the selection of most appropriate collection for association mapping (Lu et al., 2011).

Seed cotton yield, yield components and fiber quality traits in cotton has been studied by utilizing association mapping by many scientists all over the world (Abdurakhmonov et al. 2008 and 2009). Association mapping has enabled the scientists to study the variation found in the germplasm resources. With the discovery of single nucleotide polymorphism, it is now possible to study the whole genome wide association with desired quantitative trait loci for developing highly saturated mapping populations in plants (Waqas et al., 2014).

16 Linkage Maps
The chromosomes obtained from two different parents may be elucidated by using linkage maps (Paterson, 1996a). The location and relative genetic distances in either side of markers across chromosomes, which is parallel to signs along a roadway is manifested by linkage maps (Collard, et al., 2005). Genetic linkage maps are helpful in introgression, examining genome structure and MAS in plant improvement studies owing to close association with important agronomic characters (Bolek, 2003). Genetic information of a crop genome is usually presented in framework of a genetic linkage map. Such maps are useful to locate or tag genes of interest, to facilitate MAS, and to enable map-based cloning. Use of MAS to improve the resistance has become a choice for many breeding programs.

The regions in genomes having genes linked with a quantitative trait are called quantitative trait loci, QTLs (Collard et al., 2005) and QTL mapping is used for developing linkage maps and conducting QTL analysis (Paterson, 1996a). QTL mapping is accomplished by crossing over principal that allow the analysis of genes and markers in the progeny (Paterson et al. 1998). These characters are often of oligogenic inheritance in nature. Although, for some quality traits, few major QTLs or genes can account for a very high proportion of the phenotypic variation of the trait (Pham et al., 2012). Many required traits are examined at the same time by manipulating marker methodology which utilize F2, recombinant inbred lines, back-cross populations, near isogenic lines and doubled haploids (Jiang et al., 2007b). Centi Morgans (cM) transform recombination fractions into map units during mapping analysis. The investigation of many segregating markers produces linkage map. Moreover, additional markers mapping may saturate structure of maps. Marker types that produce multiple loci per primer combination like AFLPs are desired for increasing marker density. The selection of additional markers tagged to precise chromosomal regions may be observed by bulked-segregant analysis (Campbell et al., 2001). The researchers at global level has constructed many linkage maps to map functional traits and markers which consists about 5000 markers in public database inclusive 3300 restriction fragment length polymorphism (RFLP), 700 amplified length polymorphism (AFLP), 1000 microsatellites and 100 single nucleotide polymorphism (Rahman et al., 2012).

Jiang et al. (1998) developed an RFLP map of 261 markers distributed among 26 linkage groups using F2 plants from an interspecific cross. Ulloa and Meredith (1998) constructed a map by employing RFLP markers and identified 26 QTLs for agronomic and fiber quality. QTL mapping by RFLP was observed for chlorophyll contents (Saranga et al., 2001). 75 BC1 (G. hirsutum × G. barbadense) plants were examined with 1014 markers (Lacape et al., 2003) for the construction of map. The map included 888 loci, containing 465 AFLPs, 229 SSRs, 192 RFLPs and 2 morphological markers, arranged in 37 linkage groups and covering 4400cM. 18 of the 26 long groups had a single dense region as the loci were not evenly distributed on linkage groups and they assumed a partially modified list of 13 homologous pairs of chromosomes of tetraploid cotton genome. Rahman et al. (2002) observed molecular markers connected with nectariless, hairiness and red color spots. Saranga et al., (2001, 2004); Paterson et al., (2003); Chee et al., (2005b); Draye et al., (2005) developed linkage map having 432 QTLs (yield and fiber quality, leaf and flower morphology, trichome density and their distribution etc.) and 3475 loci detected in 11 populations.

Execution of desired molecular assisted selection includes a dilemma, e.g breeding methodology, number of individuals in a population, target loci desired etc (Bonnet et al.,2005) and also use inbreeding, F2 enrichment and backcrossing techniques. To obtain efficient and fast cotton improvement at global level with high seed cotton yield and better fiber quality; cotton molecular assisted selection methodology has been explored vastly in genomics (Zhang et al., 2008; Paterson et al., 2012; Wang et al., 2013) and a tremendous achievement has been accomplished. High saturated map can be developed with the markers which are polymorphic between near isogenic lines and the donor parent should express markers that are tagged to target gene. Stelly et al., 2005 produced alien chromosome substitution lines in a near isogenic genetic background of TM-1 by implying hyponeuploid-based backcross. Moreover, chromosome effects on enhancement in lint yield and fiber quality traits by using CS-B lines have been examined by scientists (Saha et al., 2006; Jenkins et al., 2006).

Recently Cao et al. (2014) investigated the first practical use of chromosome segment introgression lines (CSILs) for the transfer of fiber quality QTLs into upland cotton cultivars using SSR markers without severally effecting the economic traits. Microsatellite sequences mutate frequently by slippage and proofreading errors during DNA replication that primarily change the number of repeats and thus the length of the repeat string (Eisen, 1999). Recent advances in next-generation sequencing technologies have provided cost effective platforms for direct detection of high-quality single nucleotide polymorphisms (SNP) markers for genotyping of mapping populations (Schuster, 2008; Varshney et al., 2009). Genotyping by sequencing derived genomic selection is a prominent technique for crop improvement. The value of GBS data and cost effectiveness for improving the breeding techniques via genomic selection are a lot.

17 Conclusion
Molecular markers have significant value in future cotton genetic-breeding. They offer a relatively simple method of tracing genetic sources. Specific chromosome regions with important QTLs can be identified and utilized for efficient selection strategies. Major concerns of decline in cotton productivity is genetic uniformity among cotton cultivars which do not allow for making significant genetic improvement for yield related traits, effected by biotic and abiotic stresses. This objective can be achieved by introgression and use of modern molecular technologies in increasing genetic gain of economic traits. DNA markers are the prominent types of genetic markers for molecular assisted selection. Relatively speaking, SSRs have most of the desirable features and thus are the current marker of choice for many crops. The use of SNP markers in MAS programs has been growing faster and so the development of technologies and platforms for the discovery of SNPs is important task in many crops. The application of sequence-based genotyping for a whole range of diversity and genomic studies will have an important place well into the future.


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