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

Abstract

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.

Keywords
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 (www.cottongen.org/find/mapped 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.


References

Abdalla A.M., Reddy O.U.K., El-Zik K.M., and Pepper A.E., 2001, Genetic diversity and relationships of diploid and tetraploid cottons revealed using AFLP., Theoretical and Applied Genetics, 102(2-3): 222-229
http://dx.doi.org/10.1007/s001220051639
 
Abdurakhmonov I.Y., Buriev Z., Shermatov S., Abdullaev A., Kushanov F., Abdukarimov A., Percy, R., et al., 2012, Cotton genomics and transgenomics in Uzbekistan, Proceedings of The International Cotton Genome Initiative 2012 Conference
 
Abdurakhmonov I.Y., Buriev Z.T., Shermatov S.E. et al., 2011, Marker-assisted selection for complex fiber traits in cotton, 5th World Cotton Research Conference, Spaecial session of ICGI, Mumbai, India
 
Abdurakhmonov I.Y., Kohel R.J., Yu J.Z., Pepper A.E., Abdullaev A.A., Kushanov F.N., Salakhutdinov I.B., Buriev Z.T., Saha S., Scheffler B.E., Jenkins J.N., and Abdukarimov A., 2008, Molecular diversity and association mapping of fiber quality traits in exotic G. hirsutum L. germplasm, Genomics, 92(6): 478-487
http://dx.doi.org/10.1016/j.ygeno.2008.07.013
 
Abdurakhmonov I.Y., Saha S., Jenkins J.N., Buriev Z.T., Shermatov S.E., Scheffler B.E., Pepper A.E., Yu J.Z., and Kohel R.J., 2009, Linkage disequilibrium based association mapping of fiber quality traits in G. hirsutum L. variety germplasm, Genetica, 136(3):401-417
http://dx.doi.org/10.1007/s10709-008-9337-8
 
Ablet G., Hill H., and Henary R.J., 2006, Sequence polymorphism discovery in wheat microsatellite flanking regions using pyrophosphate sequencing, Molecular Breeding, 17(3): 281-289
http://dx.doi.org/10.1007/s11032-006-6262-3
 
Agarwal M., Shrivastava N., and Padh H., 2008, Advances in molecular marker techniques and their applications in plant sciences, Plant Cell Reports, 27(4): 617-631
http://dx.doi.org/10.1007/s00299-008-0507-z
 
Altaf M.K., Stewart J.M., Wajahatullah M.K., Zhang J.F., and Cantrell R.G., 1997, Molecular and morphological genetics of a trispecies F2 population of cotton, In: Dugger P., and Richter D.A., (eds.), Reprinted from the Proceedings of the Beltwide Cotton, National Cotton Council, Memphis TN, San Diego California, USA, pp.448-452
 
Andersen J.R., and Lubberstedt T., 2003, Functional markers in plants, Trends in Plant Science, 8(11):554-560
http://dx.doi.org/10.1016/j.tplants.2003.09.010
 
Appleby N., Edwards D., and Batley J., 2009, New technologies for ultra-high throughput genotyping in plants, Methods in Molecular Biology, 513:19-39
http://dx.doi.org/10.1007/978-1-59745-427-8_2
 
Arunita R., Rakshit S., Santhy V., Gotmare V.P., et al., 2010, Evaluation of SSR markers for the assessment of genetic diversity and fingerprinting of Gossypium hirsutum accessions. J. Plant Biochem. Biot. 19: 153-160
 
Aslam M., Jiang C., Wright R., and Paterson A.H., 1999, Identification of molecular markers linked to leaf curl virus disease resistance in cotton, Pakistan Journal Biological Sciences, 2(1): 124-126
http://dx.doi.org/10.3923/pjbs.1999.124.126
 
Ayeh K.O., 2008, Expressed sequence tags (ESTs) and single nucleotide polymorphisms (SNPs): Emerging molecular marker tools for improving agronomic traits in plant biotechnology, African Journal of Biotechnology, 7(4): 331-341
 
Baird N.A., Etter. P.D., Atwood T.S., Currey M.C., Shiver A.L., Lewis Z.A., Selker E.U., Cresko W.A., Johnson E.A.,and 2008, Rapid SNP discovery and genetic mapping using sequenced RAD markers, PLoS One, 3(10)
http://dx.doi.org/10.1371/journal.pone.0003376
 
Batley J., and Edwards D., 2007, SNP applications in plants, In: Oraguzie N.C., Rikkerink E.H.A., Gardiner S.E., and Silva D., (eds.), Association Mapping in Plants, Springer, NY, pp.95-102
http://dx.doi.org/10.1007/978-0-387-36011-9_6
 
Beasley J.O., 1940, The origin of American tetraploid Gossypium species, American Naturalist, 74: 285-286
http://dx.doi.org/10.1086/280895
 
Berard A., Le Paslier M.C., Dardevet M., Exbrayat V.F., Bonnin I., Cenci A., Haudry A., Brunel D., and Ravel C., 2009, High-throughput single nucleotide polymorphism genotyping in wheat (Triticum spp.), Plant Biotechnology Journal, 7(4): 364-374
http://dx.doi.org/10.1111/j.1467-7652.2009.00404.x
 
Bernardo R., 2008, Molecular markers and selection for complex traits in plants: learning from the last 20 years, Crop Science, 48(5): 1649-1664
http://dx.doi.org/10.2135/cropsci2008.03.0131
Bidichandani S.I., Ashizawa T., and Patel P.I., 1998, The GAA triplet-repeat expansion in Friedreich ataxia interferes with transcription and may be associated with an unusual DNA structure, The American Journal of Human Genetics, 62(1): 111-121
http://dx.doi.org/10.1086/301680
 
Billotte N., Risterucci A.M., Barcelos E., Noyer J.L., Amblard P., and Baurens F., 2001, Development, characterization, and across-taxa utility of oil palm (Elaeis guineensis Jacq.) microsatellite markers, Genome, (44): 413-425
http://dx.doi.org/10.1139/gen-44-3-413
http://dx.doi.org/10.1139/g01-017
 
Blake T.K., Kadyrzhanova D., Shepherd K.W., Islam A.K., Langridge P.L., McDonald C.L., and Talbert L.E., 1996, STS PCR markers appropriate for wheat-barley introgression, TAG Theoretical and Applied Genetics, 93(5): 826-832
http://dx.doi.org/10.1007/BF00224082
 
Bolek Y., 2003, Status of Genome Mapping and Use in Cotton Improvement, KSÜ Fen ve Mühendislik Dergisi, 6(2):72-79
 
Bolek Y., El-Zik K.M., Pepper A.E., Bell A.A., Magill C.W., Thaxton P.M and Reddy O.U.K., 2005, Mapping of verticillium wilt resistance genes in cotton, Plant Science, 168(6):1581-1590
http://dx.doi.org/10.1016/j.plantsci.2005.02.008
 
Bonnet J., Fraile A., Sacristan S., Malpica J.M., and Garcı’a-Arenal F., 2005, Role of recombination in the evolution of natural populations of Cucumber mosaic virus, a tripartite RNA plant virus, Virology, 332(1): 359-368
http://dx.doi.org/10.1016/j.virol.2004.11.017
 
Bornet B., and Branchard M., 2001, Non-anchored inter simple sequence repeat (ISSR) markers: Reproducible and specific tools for genome fingerprinting, Plant Molecular Biology Reporter, 19(3): 209-215
http://dx.doi.org/10.1007/BF02772892
 
Bornet B., Muller C., Paulus F., and Branchard M., 2002, Highly informative nature of inter simple sequence repeat (ISSR) sequences amplified using tri and tetra-nucleotide primers from DNA of cauliflower (Brassica oleracea var. botrytis L.), Genome, 45(5): 890-896
http://dx.doi.org/10.1139/g02-061
 
Bundock P.C., Cross M.J., Shapter F.M., and Henry R.J., 2006, Robust allele specific polymerase chain reaction markers developed for single nucleotide polymorphisms in expressed barley sequences, Theortical and Applied Genetics, 112(2): 358-365
http://dx.doi.org/10.1007/s00122-005-0137-6
 
Byers R.L., Harker D.B., Yourstone S.M., Maughan P.J., and Udall J.A., 2012, Development and mapping of SNP assays in allotetraploid cotton, Theortical and Applied Genetics, 124(7): 1201-1214
http://dx.doi.org/10.1007/s00122-0111780-8
 
Campbel K.G., Finey P.L., Bergman C.J., Gualberto D.G., Anderson J.A., Giroux M.J., Sirtunga D., and Sorels M.E., 2001, Quantiative trait loci asociated with miling and baking quality in a soft x hard wheat cros, Crop Science, 41(4): 1275-1285
http://dx.doi.org/10.2135/cropsci2001.4141275x
 
Cao Z., Wang P., Zhu X., Chen H., and Zhang T., 2014, SSR marker assisted improvement of fiber qualities in Gossypium hirsutum using Gossypium barbadense introgression, Theortical and Applied Genetics, 127(3): 587-594
http://dx.doi.org/10.1007/s00122-013-2241-3
 
Chee P., Draye X., Jiang C.X., Decanini L., Delmonte T.A., Bredhauer R., Smith C.W., and Paterson A.H., 2005, Molecular dissection of interspecific variation between Gossypium hirsutum and Gossypium barbadense (cotton) by a backcross-self approach: I. Fiber elongation, Theortical and Applied Genetics, 111(4): 757-763
http://dx.doi.org/10.1007/s00122-005-2062-0
http://dx.doi.org/10.1007/s00122-005-2063-z
 
Chen Z.J., Scheffler B.E., Dennis E., Triplett B.A., Zhang T., Guo W., Chen X., Stelly D.M., Rabinowicz P.D., Town C.D., Arioli T., Brubaker C., Cantrell R.G., Lacape J.M., Ulloa M., Chee P., Gingle A.R., Haigler C.H., Percy R., Saha S., Wilkins T., Wright R.J., Van Deynze A., Zhu Y., Yu S., Abdurakhmonov I., Katageri I., Kumar P.A., Mehboob-Ur-Rahman., Zafar Y., Yu J.Z., Kohel R.J., Wendel J.F., and Paterson A.H., 2007, Towards sequencing cotton (Gossypium) genomes, Plant Physiology, 145(4): 1303-1310
http://dx.doi.org/10.1104/pp.107.107672
 
Ching A.D.A., Caldwell K.S., Jung M., Dolan M., Smith O., Tingey S., Morgante M., and Rafalski A.J., 2002, SNP frequency, haplotype structure and linkage disequilibrium in elite maize inbred lines, BMC Genetics 3(1): 1
http://dx.doi.org/10.1186/1471-2156-3-1
http://dx.doi.org/10.1186/1471-2156-3-19
http://dx.doi.org/10.1186/1471-2350-3-1
http://dx.doi.org/10.1186/1471-2164-3-1
 
Choi I.Y., Hyten D.L., Matukumalli L.K., Song Q., Chaky J.M., Quigley C.V., Chase K., Lark G., Reiter r.s., Yoon M., Hwang E.Y., Young N.D., Yi S.I., Shoemaker R S.,Tassell C.P., Specht J.E., and Cregan p.b., 2007, A soybean transcript map: gene distribution, haplotype and single nucleotide Polymorphism analysis, Genetics 176(1): 685-696
http://dx.doi.org/10.1534/genetics.107.070821
 
Coetes D.J., and Byrne M., 2005, Genetic variation in plant populations, In: Henry R.J, (ed.) Plant diversity and Evolutions Genotypic and phenotypic variation in higher plants, CABI Publishing,Wallingford, Oxfordshire, UK, pp. 139-164
http://dx.doi.org/10.1079/9780851999043.0139
 
Collard B.C.Y., and Mackill D.J., 2008, Marker assisted selection: an approach for precision plant breeding in the twenty- first century, Philosophical Transactions of the Royal Society of London B: Biological sciences, 363(1491): 557-572
http://dx.doi.org/10.1098/rstb.2007.2170
 
Collard B.C.Y., Jahufer M.Z.Z., Brouwer J.B., and 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
http://dx.doi.org/10.1007/s10681-005-1681-5
 
Cuadrado A., and Schwardzacher T., 1998, The chromosomal organization of simple sequence repeats in wheat and rye genomes. Chromosoma 107(8): 587-594
http://dx.doi.org/10.1007/s004120050345
 
Cuming D.S., Altan F., Akdemir H., Tosun M., Gurel A., and Tanyolac B., 2015, QTL analysis of fiber color and fiber quality in naturally green colored cotton (Gossypium hirsutum L.). Turkish Journal. of Field Crops, 20(1): 49-58
 
Deynze A.V., Stoffel K., Lee M., Wilkins T.A., Kozik A., Cantrell R.G., Yu J.Z., Kohel R., and Stelly D.M., 2009, Sampling nucleotide diversity in cotton, BMC Plant Biology, 9(1):125
http://dx.doi.org/10.1186/1471-2229-9-125
 
Dongre A.B., Bhandarkar M., and Banerjee S., 2007, Genetic diversity in tetraploid and diploid cotton (Gossypium spp.) using ISSR and microsatellite DNA markers, Indian Journal of . Biotechnology, 6: 349-353
 
Draye X., Chee P., Jiang C.X., Decanini L., Delmonte T.A., Bredhauer R., Smith C.W and Paterson, A.H., 2005, Molecular dissection of interspecific variation between Gossypium hirsutum and G. barbadense (cotton) by a backcross-self approach: II. Fiber fineness, Theoretical and Applied Genetics, 111(4):764-771
http://dx.doi.org/10.1007/s00122-005-2061-1
 
Edwards D., and Batley J., 2010, Plant genome sequencing: applications for crop improvement, Plant Biotechnology Journal, 8(1): 2-9
http://dx.doi.org/10.1111/j.1467-7652.2009.00459.x
 
Eisen J., 1999, Mechanistic explanations for variation in microsatellite stability within and between species, In: Goldstein D. and Schlötterer, C. (eds.), Microsatellites: Evolution and Applications, Oxford University Press, Oxford, pp. 34-48
 
Elshire R.J., Glaubitz J.C., Sun Q., Poland J.A., Kawamoto K., Buckler E.S, and Mitchell S.E., 2011, A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species, PLoS One, 6(5)
http://dx.doi.org/10.1371/journal.pone.0019379
 
Enrique Viguera E., Canceill D., and Ehrlich S.D., 2001, Replication slippage involves DNA polymerase pausing and dissociation,The EMBO Journal, 20(10): 2587-2595
http://dx.doi.org/10.1093/emboj/20.10.2587
 
Feng C.D., Stewart J.M.D., and Zhang J.F., 2005, STS markers linked to the Rf1 fertility restore gene of cotton, Theoretical Applied Genetics, 110(2): 237-243
http://dx.doi.org/10.1007/s00122-004-1817-3
 
Frelichowski Jr.J.E., Palmer M.B., Main D., Tomkins J.P., Cantrell R.G., Stelly D.M., Yu J., Kohel R.J.,and Ulloa M., 2006, Cotton genome mapping with new microsatellites from Acala 'Maxa' BAC-ends. Molecular Genetics and Genomics, 275(5): 479-491
http://dx.doi.org/10.1007/s00438006-0106-z
 
Gao L.F., Jing L.R., Huo N.X., Li Y., Li X.P., Zhou R.H., Chang X.P., Tang Z.Y.M., and Jia J.Z.,2004, One hundred and one new microsatellite loci derived from ESTs (EST-SSRs) in bread wheat, Theoretical Applied Genetics, 108(7): 1392-1400
http://dx.doi.org/10.1007/s00122-003-1554-z
 
Geng C.D., Gong Z.Z., Huang J.Q., and Zhang Z.C., 1995, Identification of difference between cotton cultivars (G. hirsutum) using the RAPD method, Jiangsu Journal Agricultural Sciences, 11(4): 21-24
 
Gore M.A., Fang D.D., Poland J.A., Zhang J., Percy R.G., Cantrell R.G., Thyssen G., and Lipka A.E., 2014, Linkage Map Construction and Quantitative Trait Locus Analysis of Agronomic and Fiber Quality Traits in Cotton, The Plant Genome, 7(1)
http://dx.doi.org/10.3835/plantgenome2013.07.00
 
Grover C.E., Zhu X., Grupp K.K., Jareczek J.J., Gallagher J.P., Szadkowski E., Seijo J.G., Wendel J.F., 2014. Molecular confirmation of species status for the allopolyploid cotton species, Gossypium ekmanianum Wittmack. Genet. Resour. Crop Evol., 1–12.
 
Guo W., Zhang T., Shen X., Yu Z.J., and Kohel R.J., 2003, Development of SCAR Marker Linked to a Major QTL for High Fiber Strength and Its Usage in Molecular-Marker Assisted Selection in Upland Cotton, Crop Science, 43(6): 2252-2256
http://dx.doi.org/10.2135/cropsci2003.2252
 
Guo W.Z., Cai C.P., Wang C.B., Han Z.G., Song X.L., Wang K., Niu X.W., Wang C., Lu K.Y., and Zhang T.Z., 2007, A microsatellite-based, gene-rich linkage map reveals genome structure, function and evolution in Gossypium, Genetics, 176(1): 527-541
http://dx.doi.org/10.1534/genetics.107.070375
 
Gupta PK, Varseny RK, Sharma PC, Ramesh B. 1999. Molecular markers and their application in bwheat breeding. Plant Breed. 118:369-390
 
Han Z.G., Guo W.Z., Song X.L., and Zhang T.Z., 2004, Genetic mapping of EST-derived microsatellites from the diploid Gossypium arboreum in allotetraploid cotton, Molecular Genetics and Genomics, 272(3): 308-327
http://dx.doi.org/10.1007/s00438-004-1059-8
 
Hart D.L., and Clark A.G., eds., 1997, Principles of Population Genetics, Sinauer Associates, Sunderland, Massachusetts, pp.1-635
Hearne S.J., Lorenzen J., Town C., and Zhuang E., 2008, EST derived genomic resources for Musa, IITA Report, www.IITA.org
 
Helentjaris T., Slocum M., Wright S., Schaefer A., and Nienhuis J., 1986, Construction of genetic linkage maps in maize and tomato using restriction fragment length polymorphisms, Theoretical and Applied Genetics, 72(6):761-769
http://dx.doi.org/10.1155/2014/607091
 
Huang X.H., Wei X.H., Sang T., Zhao Q., Feng Q., Zhao Y., Li C.Y., Zhu C.R., Lu T.T., Zhang Z.W., Li M., Fan D.L., Guo Y.L., Wang A.H., Wang L., Deng L.W., Li W.J., Lu Y.Q., Huang T., Zhou T.Y., Jing Y.F., Li W., Lin Z., Buckler E.S., Qian Q., Zhang Q.F., Li J.Y., and Han B., 2010, Genome wide association studies of 14 agronomic traits in rice landraces, Nature Genetics, 42(11):961-967
http://dx.doi.org/10.1038/ng.695
 
Hussein E.H.A., Adawy S S., Ismail S., and El-Itriby H.A. 2005, Molecular characterization of some Egyptian date palm germplasm using RAPD and ISSR markers, Arab Journal of Biotechnology, 8(1): 83-98
 
Ichikawa N., Kishimoto N., Lnagaki A., Nakamura A., Koshino Y., Yokozeki Y., Oka M., Samoto S., Akagi H., Higo K., Shinjyo C., Fujimura T., and Shimada H., 1997, A rapid PCR-aided selection of a rice line containing the Rf-1 gene which is involved in restoration of the cytoplasmic male sterility, Molecular Breeding, 3(3):195-202
http://dx.doi.org/10.1023/A:1009601007175
 
Iqbal M.J., Reddy O.U.K., El-Zik K.M., and Pepper A.E., 2001, A genetic bottleneck in the evolution under domestication of upland cotton Gossypium hirsutum L. examined using DNA fingerprinting, Theoretical and Applied Genetics, 103(4): 547-554
http://dx.doi.org/10.1007/PL00002908
 
Jander G., Norris S R., Rounsley S.D., Bush D.F., Levin I.M., and Last R.L., 2002, Arabidopsis mapbased cloning in the post-genome era, Plant Physiology, 129(2): 440-450
http://dx.doi.org/10.1104/pp.003533
 
Jenkins J. N., Wu J., McCarty J.C., Saha S., Gutierrez O.A., Hayes R., and Stelly D.M., 2006, Genetic effects of thirteen Gossypium barbadense L. chromosome substitution lines with Upland cotton cultivars: I. Yield and yield component, Crop Science, 46(3): 1169-1178
http://dx.doi.org/10.2135/cropsci2005.08-0269
 
Jiang C.X., Chee P.W., Draye X., Morrell P.L., Smith C.W., and Paterson A.H., 2000, Multilocus interactions restrict gene flow in advance generation interspecific populations of polyploid Gossypium (cotton), Evolution, 54(3): 798-814
http://dx.doi.org/10.1554/0014-3820(2000)054[0798:MIRGII]2.3.CO;2
http://dx.doi.org/10.1111/j.0014-3820.2000.tb00081.x
 
Jiang C.X., Wright R.J., El-Zik K.M., and Paterson A.H., 1998, Polyploid formation created unique avenues for response to selection in Gossypium (Cotton), Proceeding of the National Academy of Sciences, 95(8): 4419-4424
http://dx.doi.org/10.1073/pnas.95.8.4419
 
Jiang G.L., Dong Y., Shi J., and Ward R.W., 2007, QTL analysis of resistance to Fusarium head blight in the novel wheat germplasm CJ 9306. II. Resistance to deoxynivalenol accumulation and grain yield loss. Theoretical Applied Genetics, 115(8): 1043-1052
http://dx.doi.org/10.1007/s00122-007-0630-1
 
Joshi C.P., and Nguyen H.T., 1993, RAPD (random amplified polymorphic DNA) analysis based inter varietal genetic relationships among hexaploid wheats, Plant Science, 93(1): 95-103
http://dx.doi.org/10.1016/0168-9452(93)90038-2
 
Jubrael J.M., Udupa S.M., and Baum M., 2005, Assessment of AFLP-based genetic relationships among date palm (Phoenix Dactylifera L.) varieties of Iraq, Journal of the American Society Horticultural Science, 130(3): 442-447
 
Kalia R.K., Rai M.K., Kalia S., Singh R., and Dhawan, A.K., 2011, Microsatellite markers: an overview of the recent progress in plants, Euphytica, 177(3): 309-334
http://dx.doi.org/10.1007/s10681-010-0286-9
 
Kantety R.V., La Rota M., Matthews D.E., and Sorrells M.E., 2002, Data mining for simple-sequence repeats in expressed sequence tags from barley, maize, rice, sorghum, and wheat, Plant Molecular Biology, (48): 501-510
http://dx.doi.org/10.1023/A:1014875206165
 
Karaca M., and Ä°nce A.G., 2011, New non-redundant microsatellite and CAPS- microsatellite markers for cotton (Gossypium L.), Turkish Journal of Field Crops, 16(2): 172-178
 
Khan S.A., Hussain D., Askari E., Stewart J.M., Malik K.A., and Zafar, Y., 2000, Molecular phylogeny of Gossypium species by DNA fingerprinting. Theoretical and Applied Genetics, 101(5-6): 931-938
http://dx.doi.org/10.1007/s001220051564
 
Khanam S., Sham A., Bennetzen J.L., and Aly M.A.M., 2012, Analysis of molecular marker-based characterization and genetic variation in date palm (Phoenix dactylifera L.), Australian Journal of Crop Science, 6(8): 1236-1244
 
King R.C., and Stansfield W.D., 1990, A dictionary of genetics, Oxford University Press, New York, pp.188
 
Koebner R.M.D., and Summers R.W., 2003, 21st century wheat breeding: plot selection or plate detection? Trends in Biotechnology, 21(2): 59-63 doi: 10.1016/S0167-7799(02)00036-7
http://dx.doi.org/10.1016/S0167-7799(02)00036-7
 
Kumar L.S., 1999, DNA markers in plant improvement: an overview, Biotechnology Advances, 17(2): 143-182
http://dx.doi.org/10.1016/S0734-9750(98)00018-4
 
Kumpatla S.P., Buyyarapu R., Abdurakhmonov I.Y., and Mammadov J.A., 2012, In: Abdurakhmonov I.Y., (ed.), Genomics-Assisted Plant Breeding in the 21st Century: Technological Advances and Progress, Plant Breeding, In Tech, Croatia, pp.131-184
 
Lacape J.M., Dessauw D., Rajab M., Noyer J.L., and Hau B., 2007, Microsatellite diversity in tetraploid Gossypium germplasm: assembling a highly informative genotyping set of cotton SSRs, Molecular Breeding 19(1): 45-58
http://dx.doi.org/10.1007/s11032-006-9042-1
 
Lacape J.M., Nguyen T.B, Thibivilliers S., Bojinov B., Courtois B., Cantrell R.G., Burr B and Hau B., 2003, A combined RFLP-SSR-AFLP map of tetraploid cotton based on a Gossypium hirsutum x Gossypium barbadense backcross population, Genome, 46(4): 612-626
http://dx.doi.org/10.1139/g03-050
 
Li F.G., Fan G.Y., Wang K.B., Sun F.M., Yuan Y.L., Song G.L., Li Q., Ma Z.Y., Lu C.R., Zou C.S., Chen W.B., Liang Z.M., Shang H.H., Liu W.Q., Shi C.C., Xiao G.H., Gou C.Y., Ye W.W., Xu X., Zhang X.Y., Wei H.L., Li Z.F., Zhang G.Y., Wang J.Y., Liu K., Kohel R.J., Percy R.G., Yu J.Z., Zhu Y.X., Wang J., and Yu S.X., 2014, Genome sequence of the cultivated cotton Gossypium arboreum, Nature Genetics 46(6): 567-572
http://dx.doi.org/10.1038/ng.2987
 
Lin Z.X., Zhang Y.X., Zhang X.L and Guo X.P., 2009, A high-density integrative linkage map for Gossypium hirsutum, Euphytica 166(1): 35-45
http://dx.doi.org/10.1007/s10681-008-9822-2
 
Lindblad-Toh K., Winchester, E., Daly M.J., Wang D.G., Hirschhorn J.N., Laviolette J.P., Ardlie K., Reich D.E., Robinson E., Sklar P., Shah N., Thomas D., Fan J.B., Gingeras T., Warrington J., Patil N., Hudson T.J., and Lander E.S., 2000, Large-scale discovery and genotyping of single-nucleotide polymorphisms in the mouse, Nature Genetics 24(4): 381-386
http://dx.doi.org/10.1038/74215
 
Liu D.Q., Guo X.P., Lin Z.X., Nie Y.C., and Zhang X.L., 2006, Genetic diversity of Asian Cotton (Gossypium arboreum L.) in China evaluated by microsatellite analysis, Genetic Resources and Crop Evolution, 53(6): 1145-1152
http://dx.doi.org/10.1007/s10722-005-1304-y
 
Liu R.Z., Wang B.H., Guo W.Z. Qin Y.S., Wang L.G., Zhang Y.M., and Zhang T.Z., 2012, Quantitative trait loci mapping for yield and its components by using two immortalized populations of a heterotic hybrid in Gossypium hirsutum L, Molecular Breeding, 29(2): 297-311
http://dx.doi.org/10.1007/s11032-011-9547-0
 
Liu Z., Sun Q., Ni Z., Yang T.,and Mclntosh R.A., 1999, Development of SCAR markers linked to the Pm21 gene conferring resistance to powdery mildew in common wheat, Plant Breeding, 118(3): 215-219
http://dx.doi.org/10.1046/j.1439-0523.1999.118003215.x
 
Lin ZX, He DH, Zhang XL, Nie YC, Guo XP, Zhang XL. 2005 Linkage map construction and mapping QTLs for cotton fiber quality using SRAP, SSR and RAPD. Plant Breed, 124:180-187
 
Lu H., and Myers G., 2002, Genetic relationships and discrimination of ten influential upland cotton varieties using RAPD markers, Theoretical and Applied Geneticis, 105(2-3): 325-331
http://dx.doi.org/10.1007/s00122-002-0947-8
 
Lu Y.L., Shah T., Hao Z.F., Taba S., Zhang S.H., Gao S.B., Liu J., Cao M.J., Wang J., Prakash A.B., Rong T.Z., and Xu Y.B., 2011, Comparative SNP and Haplotype Analysis Reveals a Higher Genetic Diversity and Rapider LD Decay in Tropical than Temperate Germplasm in Maize, PLoS ONE, 6(9)
http://dx.doi.org/10.1371/journal.pone.0024861
 
Lynch M., and Walsh B., 1998, Genetics and Analysis of Quantitative Traits, Sinauer, Sunderland, MA
 
Mackill D.J., Nguyen H.T., and Zhang J., 1999, Use of molecular markers in plant improvement programs for rainfed lowland rice, Field Crops Research, 64(1): 177-185
http://dx.doi.org/10.1016/S0378-4290(99)00058-1
 
Malik M., Ashraf J., Qayyum A., Ahmad M.Q, Iqbal M.Z, Khan A.A., Abid M.A., Noor E., and Abbasi G.H., 2014, Molecular Markers and Cotton Genetic Improvement: Current Status and Future Prospects, The Scientific World Journal
http://dx.doi.org/10.1155/2014/607091
 
Masterson J., 1994, Stomatal size in fossil plants: evidence for polyploid in majority of angiosperms, Science-AAAS-Weekly Paper Edition-including Guide to Scientfic Information, 264(5157): 421-424
http://dx.doi.org/10.1126/science.264.5157.421
 
Matsumoto A., and Tsumura Y., 2004, Evaluation of cleaved amplified polymorphic sequence markers for Chamaecyparis obtuse based on expressed sequence tag information from Cryptomeria japonica, Theoretical and Applied Genetics 110(1): 80-91
http://dx.doi.org/10.1007/s00122-004-1754-1
 
Mackill, D. J., Nguyen, H. T. & Zhang, J. 1999 Use of molecular markers in plant improvement programs for rainfed lowland rice. Field Crops Res. 64, 177–185. (doi:10. 1016/S0378-4290(99)00058-1)
 
Meyer L., MacDonald S., and Kiawy J., 2013, Cotton and wool outlook, Economic Research Service,USDA
 
Michelmore R.W., Paran I., and Kesseli R.V., 1991, Identification of markers linked to disease resistance gene by bulk segregant analysis: A rapid methods to detect markers in specific genome region using segregating populations, Proceedings of the National Academy of Sciences., 88(21): 9828-9832
http://dx.doi.org/10.1073/pnas.88.21.9828
 
Mishra K.K., Fougat R.S., Ballani A., Thakur V., Yachana J and Bora M., 2014, Potential and application of molecular markers techniques for plant genome analysis, International Journal of Pure and Applied Bioscience, 2 (1): 169-188
 
Nair S., Bentur J.S, Rao U.P., and Mohan M., 1995, DNA markers tightly linked to a gall midge resistance gene (Gm2) are potentially useful for marker-aided selection in rice breeding, Theoretical Applied Genetics 91(1):68-73
http://dx.doi.org/10.1007/BF00220860
 
Norio I., 1997, A rapid PCR-aided selection of a rice line containing the 863 project in China (2001AA211101), the National Trans- the–Rf-1 gene which is involved in restoration of the cytoplasmic genic Program in China (J99-A-023), and The Natural Science male sterility. Mol. Breed. 3:195–202
 
Noormohammadi Z., Hasheminejad-Ahangarani F.A., Sheidai M., Ghasemzadeh-Baraki S., and Alishah O., 2013, Genetic diversity analysis in Opal cotton hybrids based on SSR, ISSR, and RAPD markers, Genetics and Molecular Research:GMR, 12(1): 256-269
http://dx.doi.org/10.4238/2013.January.30.12
 
Noormohammadi Z., Shojaei-Jesvaghani F., Sheidai M., Farahani F., and Alishah O., 2013, Inter simple sequence repeats (ISSR) and random amplified polymorphic DNA (RAPD) analyses of genetic diversity in Mehr cotton cultivar and its crossing progenies, African Journal of Biotechnology, 10(56): 11839-11847
 
Paran I., and Michelmore R.W., 1993, Development of reliable PCR based markers linked to downy mildew resistance genes in lettuce, Theoretical and Applied Genetics, 85(8):985-993
http://dx.doi.org/10.1007/BF00215038
 
Paterson A.H., 1996, Making genetic maps. In: A.H. Paterson (ed.), Genome Mapping in Plants, San Diego, California, Academic Press, Austin, Texas, pp. 23-39
 
Paterson A.H., Lander E.S., Hewitt J.D., Peterson S., Lincoln S.E., and Tanksley S.D., 1988, Resolution of quantitative traits into Mendelian factors by using a complete linkage map of restriction fragment length polymorphisms, Nature, 335(6192): 721-726
http://dx.doi.org/10.1038/335721a0
 
Paterson A.H., Saranga Y., Menz M., Jiang C.X., and Wright R.J., 2003, QTL analysis of genotype x environment interactions affecting cotton fiber quality, Theoretical and Applied Genetics, 106(3): 384-396
 
Pham A.T., Shannon J.G., and Bilyeu K.D., 2012, Combinations of mutant FAD2 and FAD3 genes to produce high oleic acid and low linolenic acid soybean oil, Theoretical and Applied Genetics, 125(3): 503-515
http://dx.doi.org/10.1007/s00122-012-1849-z
 
Poland J.A., and Rife T.W., 2012, Genotyping-by-sequencing for plant breeding and genetics, The Plant Genome, 5(3): 92-102
http://dx.doi.org/10.3835/plantgenome2012.05.0005
 
Poland J.A., Brown P. J., Sorrells M.E and Jannink J.L., 2012, Development of high-density genetic maps for barley and wheat using a novel two enzyme genotyping-by-sequencing approach, PLoS One, 7(2)
http://dx.doi.org/10.1371/journal.pone.0032253
 
Qin H.D., Chen M., Yi X.D., Bie S., Zhang C., Zhang Y.C., Lan J.Y., Yuan Y.L., and Jiao C., 2015, Identification of Associated SSR Markers for Yield Component and Fiber Quality Traits Based on Frame Map and Upland Cotton Collections, PLoS One, 10(1) doi:10.1371/journal.pone.0118073
http://dx.doi.org/10.1371/journal.pone.0118073
 
Queller D.C., Strassmann J.E., and Hughes C.R., 1993, Microsatellites and kinship, Trenhs in Ecology and Evolution., 8(8): 285-288
http://dx.doi.org/10.1016/0169-5347(93)90256-O
 
Qureshi S.N., Saha S., Kantety R.V., and Jenkins J.N., 2004, Molecular biology and physiology: EST-SSR:a new class of genetic markers in cotton, Journal of Cotton Science, 8: 112-123
 
Rahman M., Asif M., Ullah I., Malik K.A., and Zafar Y., 2005, Overview of cotton genomic studies in Pakistan, Plant and Animal Genome Conference XIII, San Diego, USA
 
Rahman M., Hussain D., and Zafar Y., 2002, Estimation of genetic divergence among elite cotton (Gossypium hirsutum L.) cultivars/genotypes by DNA fingerprinting technology, Crop Science, 42:2137-2144
http://dx.doi.org/10.2135/cropsci2002.2137
 
Rahman M., Shaheen T., Tabbasam N., Iqbal M.A., Ashraf M., Zafar Y., and Paterson A.H., 2012, Cotton genetic resources. A review, Agronomy for Sustainble Development., 32: (2): 419-432
http://dx.doi.org/10.1007/s13593-011-0051-z
 
Rahman M., Zafar Y., and Paterson A.H., 2009, Gossypium DNA markers: types, numbers and uses, In: Paterson AH (ed.), Genetics and Genomics of Cotton, Springer, US, pp. 101-139
http://dx.doi.org/10.1007/978-0-387-70810-2_5
 
Rakshit A., Rakshit S., Santhy V., Gotmare V.P., Mohan P., Singh V.V., Singh S., Singh J., Balyan H.S., Gupta S.R., and Bhat S.R., 2010, Evaluation of SSR markers for the assessment of genetic diversity and fingerprinting of Gossypium hirsutum accessions, Journal of Plant Biochemistry and Biotechnoology, 19(2): 153-160
http://dx.doi.org/10.1007/BF03263335
 
Reamon-Buttner S.M., and Jung C., 2000, AFLP derived STS markers for the identification of sex in Asparagus officinalis L, Theoretical and Applied Genetics, 100(3-4): 432-438
http://dx.doi.org/10.1007/s001220050056
 
Reddy M.P., Sarla N., and Siddiq E.A., 2002, Inter simple sequence repeat (ISSR) polymorphism and its application in plant breeding, Euphytica, 128(1): 9-17
http://dx.doi.org/10.1023/A:1020691618797
 
Reinisch A.J., Dong J.M., Brubaker C. L., Stelly D.M., Wendel J.F., and Paterson A.H., 1994, A detailed RFLP map of cotton, Gossypium hirsutum x Gossypium barbadense: chromosome organization and evolution in a disomic polyploid genome, Genetics, 138(3): 829-847
 
Roychowhury R., Taoutaou A., Khalid R.K., Mohamed R.A.G., and Jagatpati T., 2014, Crop improvement in the ear of climate change, In: Roychowhury (eds.), I.K International Publication house Ltd.
 
Rungis D., Llewellyn D., Dennis E.S., and Lyon, B.R., 2002, Investigation of the chromosomal location of the bacterial blight resistance gene present in an Australian cotton (Gossypium hirsutum L.) cultivar, Crop and Pasture Science, 53(5):551-560
http://dx.doi.org/10.1071/AR01121
 
Russell J.R., Fuller J.D., Macaulay M., Hatz B.G., Jahoor A., Powell W., and Waugh R., 1997, Direct comparison of levels of genetic variation among barley accessions detected by RFLPs, AFLPs, SSRs and RAPDs, Theoretical and Applied Genetics 95(4): 714-722
http://dx.doi.org/10.1007/s001220050617
 
Sachidanandam R., Weissman D., Schmidt S.C., Kakol J.M., Stein L.D., Marth G., Sherry S., Mulikin J.C., Mortimore B.J., Willey D.L., Hunt S.E., Cole C.G., Coggill P.C., Rice C.M., Ning Z.M., Rogers J., Bentley D.R. Pui-Yan K., Mardis E.R., Yeh R.T., Schultz B., Cook L., Davenport R., Dante M., Fulton L., Hillier L., Waterston R.H., McPherson J.D., Gilman B., Schaffner S., Van Etten W.J., Reich D., Higgins J., Daly M.J., Blumenstiel B., Baldwin J., Stange-Thomann N., Zody M C., Linton L., Lander E.S., and Altshuler D., 2001, A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms, Nature, 409(6822): 928-933
http://dx.doi.org/10.1038/35057149
 
Saha S., Jenkins J.N., Wu J., McCarty J.C., Gutierrez O.A., Percy R.G., Cantrell R.G., and Stelly D.M.; 2006, Effect of chromosome specific introgression in Upland cotton on fiber and agronomic traits, Genetics, 172(3): 1927-1938
http://dx.doi.org/10.1534/genetics.105.053371
 
Saranga Y., Jiang C.X, Wright R.J., Yakir D., and Paterson A.H., 2004, Genetic dissection of cotton physiological responses to arid conditions and their inter-relationships with productivity, Plant Cell and Environment 27(3): 263-277
http://dx.doi.org/10.1111/j.1365-3040.2003.01134.x
 
Saranga Y., Menz M., Jiang C.X., Wright R.J., Yakir D., and Paterson A.H., 2001, Genomic dissection of genotype x environment interactions conferring adaptation of cotton to arid conditions, Genome Research, 11(12): 1988-1995
http://dx.doi.org/10.1101/gr.157201
 
Schulmann A.H., 2007, Molecular markers to assess genetic diversity, Euphytica, 158(3): 313-321
http://dx.doi.org/10.1007/s10681-006-9282-5
 
Schuster I., 2011, Marker-assisted selection for quantitative traits, Crop Breeding and Applied Biotechnology, 11: 50-55
http://dx.doi.org/10.1590/S1984-70332011000500008
 
Schuster S.C., 2008, Next-generation sequencing transforms today's biology, Nature, 200(8):16-18
 
Semagn K., Bjornstad B., and Ndjiondjop M.N., 2006, Progress and prospects of marker assisted backcrossing as a tool in crop breeding programs, African Journal of Biotechnology, 5(25): 88-2603
 
Shaheen T., Zafar Y., and Rahman M., 2010, Detection of Single Nucleotide Polymorphisms in the conserved ESTs regions of Gossypium arboreum, Electronic Journal of Biotechnology, 13(5): 1-10
http://dx.doi.org/10.2225/vol13-issue5-fulltext-19
 
Shanti M.L., George M.L.C., Cruz C.M.V., Bernardo M.A., Nelson R.J., Leung H., Banos L., Philippines, Reddy J.N., and Sridhar R., 2001, Identification of resistance genes effective against rice bacterial blight pathogen in eastern India, Plant Disease, 85(5): 506-512
http://dx.doi.org/10.1094/PDIS.2001.85.5.506
 
Sharma R., Joshi A., Maloo S.R., and Rajamani G., 2012, Assessment of Genetic Finger Printing Using Molecular Marker In Plants: A Review, Scientific Research and Impact, 1(3): 29-36
 
Sheidail M., Shahriari Z.H., Rokinzadeh H., and Nourmohammadi Z., 2007, RAPD and cytogenetic study of some tetraploid cotton (Gossypium hirsutum L) cultivars and their hybrids, Cytologia, 72(1): 77-82
http://dx.doi.org/10.1508/cytologia.72.77
 
Shen X., Guo W., Lu Q., Zhu X., Yuan Y., and Zhang T., 2007, Genetic Mapping of Quantitative Trait Loci for Fiber Quality and Yield Trait by RIL Approach in Upland cotton, Euphytica, 155(3): 371-380 
http://wenku.baidu.com/view/47bf090f76c66137ee061948.html
http://dx.doi.org/10.1007/s10681-006-9338-6
 
Sica M., Gamba G., Montieri S., Gaudio L., and Aceto S., 2005, ISSR markers show differentiation among Italian populations of Asparagus acutifolius L, BMC Genetics, 6:17
http://dx.doi.org/10.1186/1471-2156-6-17
http://dx.doi.org/10.1186/1471-2350-6-17
http://dx.doi.org/10.1186/1471-2164-6-17
 
Stelly D.M., Saha S., Raska D., Jenkins J.N., McCarty Jr J.C., and Gutierrez O.A., 2005, Registration of 17 Upland (Gossypium hirsutum) germplasm lines disomic for different G. barbadense chromosome or arm substitutions, Crop Science, 45(6): 2663-2666
http://dx.doi.org/10.2135/cropsci2004.0642
 
Struss D., and Plieske J., 1998, The use of microsatellite markers for detection of genetic diversity in barley populations, Theoretical and Applied Genetics, 97(1): 308-315
http://dx.doi.org/10.1007/s001220050900
 
Stuber C.W., Polacco M., and Senior M.L., 1999, Synergy of empirical breeding, marker-assisted selection, and genomics to increase crop yield potential, Crop Science, 39(6): 1571-1583
http://dx.doi.org/10.2135/cropsci1999.3961571x
 
Sunilkumar G., Campbell L.M., Puckhaber L., Stipanovic R.D., and Rathore K.S., 2006, Engineering cottonseed for use in human nutrition by tissue-specific reduction of toxic gossypol, Proceeding National Academy of Sciences, 103(48):18054-18059
http://dx.doi.org/10.1073/pnas.0605389103
 
Tanaka H., Fukuda N., and Shoyama Y., 2006, Identification and differentiation of Panax species are using ELISA, RAPD and Eastern blotting, Phytochemical Analysis, 17(1): 46-55
http://dx.doi.org/10.1002/pca.887
 
Tanksley S.D., Young N.D., Paterson A.H., and Bonierbale M.W., 1989, RFLP mapping in plant breeding: new tools for an old science, Nature Biotechnology, 7(3): 257-64
http://dx.doi.org/10.1038/nbt0389-257
 
Thomas W., 2003, Prospects for molecular breeding of barley. Annals of Applied Biology, 142(1): 1-12
http://dx.doi.org/10.1111/j.1744-7348.2003.tb00223
 
Tuberosa R., Salvi S., Sanguineti M.C., Maccaferri M., Giuliani S., and Landi P., 2003, Searching for quantitative trait loci controlling root traits in maize: a critical appraisal, Developments in Plant and Soil Science, 101: 35-54
http://dx.doi.org/10.1023/A:1026146615248
 
Ulloa M., and Meredith W.R. Jr, 2000, Genetic linkage map and QTL analysis of agronomic and fiber traits in an intraspecific population, Journal of Cotton Science, 4(3): 161-170
 
Ulloa M., Meredith Jr W.R., Shappley Z.W., and Kahler A.L., 2002, RFLP genetic linkage maps from four F2.3 populations and a joinmap of Gossypium hirsutum L, Theoretical and Applied Genetics, 104(2-3): 200-208
http://dx.doi.org/10.1007/s001220100739
 
Varshney R.K. Korzun V., and Borner A., 2004, Molecular maps in cereals: methodology and progress, In: Gupta P.K. and Varshney R.K., (eds.), Cereal Genomics, Kluwer Academic Publishers,Springer, Netherlands, pp: 35-82
 
Varshney R.K., Graner A., and Sorrells M.E., 2005, Genic microsatellite markers in plants: features and applications, Trends in Biotechnol 23(1): 48-55
http://dx.doi.org/10.1016/j.tibtech.2004.11.005
 
Varshney R.K., Nayak S.N., May G.D., and Jackson S.A., 2009, Next-generation sequencing technologies and their implications for crop genetics and breeding, Trends in Biotechnol, 27(9):522-530
http://dx.doi.org/10.1016/j.tibtech.2009.05.006
 
Viguera E., Canceill D., and Ehrlich S.D., 2001, Replication slippage involves DNA polymerase pausing and dissociation, The Embo Journal, 20(10): 2587-2595
http://dx.doi.org/10.1093/emboj/20.10.2587
 
Vos P., Hogers R., Bleeker M., Reijans M., Van D.L.T., Hornes M., Friters A., Pot J., Paleman J., Kuiper M., and Zabeau M., 1995, AFLP: a new technique for DNA fingerprinting, Nucleic Acids Research, 23(21): 4407- 4414
http://dx.doi.org/10.1093/nar/23.21.4407
 
Wang D.G., Fan J.B., Siao C.J. Berno A., Young P., Sapolsky R., Ghandour G., Perkins N., Winchester E., Spencer J., Kruglyak L., Stein L., Stein L., Hsie L., Topaloglou T., Hubbell E., Robinson E., Mittmann M., Shen N.P., Kilburn D., Rioux J., Nusbaum C., Rozen S., Morris M.S., Hudson T.J., Lipshutz R., Chee M., and Lander E.S., 2013, Large-scale identification, mapping, and genotyping of single- nucleotide polymorphisms in the human genome, Science, 280(5366): 1077-1082
http://dx.doi.org/10.1126/science.280.5366.1077
 
Wang Q., Fang L., Chen J.D., Hu Y., Si Z.F., Wang S., Chang L.J., Guo W.Z., and Zhang T.Z., 2015, Genome-Wide Mining, Characterization, and Development of Microsatellite Markers in Gossypium Species, Scientific reports, 5
http://dx.doi.org/10.1038/srep10638
 
Wang S., Meyer E., Mckay J.K., and Matz M.V., 2012, 2bRAD: a simple and flexible method for genome wide genotyping, Nature Methods, 9(8): 808-810
http://dx.doi.org/10.1038/nmeth.2023
 
Waqas M., Khan A.A., Ashraf J., Qayyum A., Ahmad M.Q, Iqbal M.Z, et al., 2014, Molecular Markers and Cotton Genetic Improvement: Current Status and Future Prospects. The Scientific World Journal Volume 2014, Article ID 607091, 15 pages
 http://dx.doi.org/10.1155/2014/607091
 
Weising K., Nybom H., Pfenningger M., Wolff K., and Kahl G., eds., 2005, DNA fingerprinting in plants: principles, methods, and applications, second edition, Detecting DNA variation by molecular markers, CRC Press, Boca Raton, Florida, U.S., p: 21-74
http://dx.doi.org/10.1201/9781420040043
 
Weissensteiner H., Haun M., Schonherr S., Neuner M., Forer L., Specht G., Kloss-Brandstätter A., Kronenberg F., and Coassin S., 2013, SNPflow: A Lightweight Application for the Processing, Storing and Automatic Quality Checking of Genotyping Assays, Plos One 8(3)
http://dx.doi.org/10.1371/journal.pone.0059508
 
Welsh J., and McClelland M., 1990, Fingerprinting genomes using PCR with arbitrary primers, Nucleic Acids Research, 18(24): 7213-7218
http://dx.doi.org/10.1093/nar/18.24.7213
 
Wendl G.F., Brubaker C.L., Alvarez J.P., Cronn RC., Stewart JM. 2009. Evolution and natural history of cotton genus. Paterson AH (Ed.) Genomics of cotton, plant genetics and genomics, crops and models 3, Springer New York pp 3-22
 
Williams J.G., Kubelik A.R., Livak K.J., Rafalski J.A., and Tingey S.V., 1990, DNA polymorphisms amplified by arbitrary primers are useful as genetic markers, Nucleic Acids Research, 18(22): 6531-6535
http://dx.doi.org/10.1093/nar/18.22.6531
 
Williams K.J., 2003, The molecular genetics of disease resistance in barley, Crop and Pasture Science 54(2), 1065-1079
http://dx.doi.org/10.1071/AR02219
 
Winter P., and Kahl G., 1995, Molecular marker technologies for plant improvement, World Journal of Microbiology and Biotechnology 11(4): 438-448
http://dx.doi.org/10.1007/BF00364619
 
Wright R.J., Thaxton P.M., El-Zik K.M., and Paterson A.H., 1998, D-subgenome bias of Xcm resistance genes in tetraploid Gossypium (cotton) suggests that polyploid formation has created novel avenues for evolution, Genetics, 149(4): 1987-1996
 
Xiao J., Fan D.D., Hendrix B., Bhatti M., and Cantrell R., 2010, A SNP haplotype associated with a gene resistant to Xanthomonas campestris pv. malvacearum (Race 18) in upland cotton (Gossypium hirsutum L.), Molecular Breeding, 25(4): 593-602
http://dx.doi.org/10.1007/s11032-009-9355-y
 
Ynturi P., Jenkins J.N., McCarty J.C., Gutierrez O.A., and Saha S., 2006, Association of root-knot nematode resistance genes with simple sequence repeat markers on two chromosomes in cotton, Crop Science, 46(6): 2670-2674
http://dx.doi.org/10.2135/cropsci2006.05.0319
 
Young N.D., and Tanksley S.D., 1989, RFLP analysis of the size of chromosomal segments retained around the Tm-2 locus of tomato during backcross breeding, Theoretical and Applied Genetics, 77(3): 353-359
http://dx.doi.org/10.1007/BF00305828
 
Yu J., and Kohel R.J., 1999, Cotton genome mapping and applications, Plant and Animal Genome Conference VII, 1: 17-21
 
Yu J., Wang J., Lin W., Li S.G., Li H., Zhou J., Ni P.X., Dong W., Hu S.N., Zeng C.Q., Zhang J.G., Zhang Y., Li R.Q., and Yang H.M., 2005, The Genomes of Oryza sativa: A History of Duplications, PLoS Biol 3(2)
http://dx.doi.org/10.1371/journal.pbio.0030038
 
Zahra N., Shojaei-Jesvaghani F., Sheidai m., Farahani F., and Omran A., 2011, Inter simple sequence repeats (ISSR) and random amplified polymorphic DNA (RAPD) analyses of genetic diversity in Mehr cotton cultivar and its crossing progenies. African Journal of Biotechnology Vol. 10(56): 11839-11847
http://dx.doi.org/10.1371/journal.pbio.0030038
 
Zhang, T., Y. Yuan, J. Yu, W. Guo, R. And J. Kohel. 2003. Molecular tagging of a major QTL for fiber strength in Upland cotton and its marker-assisted selection. Theor. Appl. Genet. Jan;106(2):262-8
 
Zhang D., Guo H., Kim C., Lee T.H., Li J.P., Robertson J., Wang X.Y., Wang Z.N., and Paterson A.H., 2013 CSGRqtl, a comparative quantitative trait locus database for Saccharinae grasses, Plant Physiology, 161(2): 594-599
http://dx.doi.org/10.1104/pp.112.206870
 
Zhang H.B., Li Y., Wang B., and Chee P.W., 2008, Recent advances in cotton genomics, International Journal of Plant Genomics
http://dx.doi.org/10.1155/2008/742304
 
Zhang T., Qian N., Zhu X. Chen H., Wang S., Mei H., and Zhang Y., 2013, Variations and transmission of QTL alleles for yield and fiber qualities in upland cotton cultivars developed in China, PLoS ONE, 8(2)
http://dx.doi.org/10.1371/journal.pone.0057220
 
Zhang Z.S., Hu M.C., Zhang J., Liu D.J., Zheng J., Zhang K., Wang W., and Wan Q., 2009, Construction of a comprehensive PCR-based marker linkage map and QTL mapping for fiber quality traits in upland cotton (Gossypium hirsutum L.), Molecular Breeding 24(1): 49-61
http://dx.doi.org/10.1007/s11032-009-9271-1
 
Zhang Z.S., Xiao Y.H., Luo M., Li X.B., Luo X.Y., Hou L., Li D.M., and Pei Y.,2005, Construction of agenetic linkage map and QTL analysis of fiber-related traits in upland cotton (Gossypium hirsutum L.), Euphytica, 144(1-2): 91-99
http://dx.doi.org/10.1007/s10681-005-4629-x
 
Zhao Y., Wang H., Chen W., and Li Y., 2014, Genetic Structure, Linkage Disequilibrium and Association Mapping of Verticillium Wilt Resistance in Elite Cotton (Gossypium hirsutum L.) Germplasm Population, PLoS One, 9(1)
http://dx.doi.org/10.1371/journal.pone.0086308
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