Molecular Breeding of Cotton

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Contact us at [email protected] Provisional chapter Chapter 7 Molecular Breeding of Cotton Molecular Breeding of Cotton Yuksel Bolek, Khezir Hayat, Adem Bardak and Yuksel Bolek, Khezir Hayat, Adem Bardak and Muhammad Tehseen Azhar Muhammad Tehseen Azhar Additional information is available at the end of the chapter Additional information is available at the end of the chapter http://dx.doi.org/10.5772/64593 Abstract Molecular characterization provides comprehensive information about the extent of genetic diversity, it assists for the development of an efective, highly accurate, and rapid marker‐assisted coton breeding program. Due to one of the world s leading iber crops, molecular studies of coton are being explored widely by coton researchers. Coton provides raw material to the textile industry among other products. Limitations in conventional breeding program for genetic improvement are due to the complexity and limited knowledge on economically important traits. The use of molecular markers for the detection and exploitation of DN“ polymorphism is one of the most signiicant developments in molecular genetics. In the present scenerio, coton molecular breeding has become a reliable source through the study and exploitation of its genetic diversity and due to beter understanding of the coton genomes using the next‐generation sequencing technologies. Coton breeders should utilize genomics in breeding programs for efective selection of best parents for agronomic and iber‐related traits, as well as for the development of resistance against biotic and abiotic stresses. The genomic research work could be based upon genotyping using DN“ markers, quantitative trait loci mapping, genome‐wide associations, and next‐generation sequencing. The objective of this chapter is to describe evolution as well as utilization of various molecular markers and review the contribution of marker‐assisted selection (M“S) in coton breeding. Keywords: coton, DN“ markers, genotyping by sequencing (G”S), genome‐wide as‐ sociation studies (GW“S), marker‐assisted selection (M“S) © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, and reproduction in any medium, provided the original work is properly cited. distribution, and reproduction in any medium, provided the original work is properly cited. 124 Cotton Research . Introduction Plant breeders select those plants, which looks phenotypically more promising due to the presence of desirable traits. Most of the traits are controlled by polygenes with complex nonallelic quantitative efects and environmental interactions. In most cases, despite the fact that biometrical genetics reveals the presence of additive or non‐additive efects on loci involved in the inheritance of quantitative trait, a speciic locus may not be detected [1]. Tightly linked loci with desired trait can support plant breeding program by rapid introgression of quantitative trait loci (QTL) using associated molecular markers [2]. Genomic region having genes of interest for a particular trait is designated as QTL (Quantitative Trait Loc). QTL analysis involves partioning of genetic variation in single component. So, DN“‐based molecular markers provide a tool to plant breeders for the selection of desirable plants based on genotype instead of phenotype. The expression of gene(s) individually their interaction with the climatic factors and agronomic measures can determine the cultivar adaptability [3]. Selection of new plant varieties with the desirable traits under given environmental conditions and cultural practices is the fundamen‐ tal basis of plant breeding [4], genetic variability produced in germplasm as a result of selection, which alter the inheritance patern of the traits, is quite useful to screen and select the cultivars for required traits. New cultivars have been developed by exploiting genotypes with enormous variation [5]. Rapid changes are needed in agricultural production, and biologically diverse as well as low‐input novel farming systems must be developed and employed. There is also a need for new crop varieties that are (1) iting‐in to global climate change in the present era, (2) adapted to biodiverse farming systems, and inally (3) giving more products to farmers and eventually to consumers. Coton (Gossypium spp.) is one of the most intensively cultivated species grown in more than 80 countries in varying climatic conditions [6]. Globally, coton is the ultimate source of iber for industry and provides oil to diet [7]. ”eing utmost iber manufacturing crop and the third contributor to oilseed production; China, India and US“ are top contributors for iber [8]. Gossypium genus is divided into eight genomes (“‐G and K) and comprised of 45 diploids and ive allotetraploid species which are found in the arid and semiarid regions of “frica, Central and South “merica, Galapagos, Indian subcontinent, “ustralia, “rabia, and Hawaii [9 11]. “t the beginning of the 20th century, scientists discovered that Mendelian factors controlling inheritance are organized in linear order on chromosomes. It was shown that genes could be inherited individually or in combination with other genes. The individual fragments lanking within a deined interval are known as molecular DN“ markers [12]. Precise DN“ portion with a known position on the chromosome [13], or a measurable trait that is associated with variation in DN“ sequence [14, 15] or a diference may act as a genetic marker if it identiies characteristics of an individual. Markers are broadly divided into three classes: (1) morphological markers, which themselves have phenotypic traits meaning the morphological and physiological features of plants are used to understand the genetic variation. “lthough morphological features may be indicative Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 of the phenotype, they are also highly afected by environmental factors and growth practices; (2) biochemical markers, including isozymes, which involve allelic variants of proteins/ enzymes; (3) molecular markers, manifest mutations in heredity material such as DN“s and RN“s [16 19]. Polymorphism of molecular markers shows diferentiation of homozygotes and heterozygotes [20]. Thotappilly et al. [21] refer to molecular markers as naturally occurring polymorphism, which include the proteins and nucleic acids that indicate certain diferences. The use of molecular markers in plant breeding is called marker‐assisted selection, often referred as M“S or marker‐assisted breeding (M“”) (Figure ) [4, 22]. Figure . Marker‐assisted scheme [4]. In traditional plant breeding, traits are selected depending on the phenotype, which is highly afected by the climatic factors. This approach makes the breeding a slow, expensive, and challenging process [23 25]. Practical advantages of using genetic markers, potential values of linkage maps, and exploiting for direct selection in plant breeding were begun to be studied about the 1930s [26]. Molecular markers are essential for mapping the genes of interest, M“S/ M“”, and cloning of genes using mapping‐based cloning strategies [27]. In addition, the use of molecular markers includes gene introgression through backcrossing, germplasm charac‐ terization, and phylogenetic analysis [28]. It has been observed that M“S is more eicient than conventional breeding techniques [4, 29, 30]. Selection based on genotypic structure through employment of molecular markers in the ield crops [31] has laid the foundation of M“S [32, 125 126 Cotton Research 33]. Many biological and medical science applications and studies, including genetic diversity, molecular tagging of economic traits, and procurement of heritable diseases have successfully utilized molecular markers [2, 34 37]. Thus far, molecular markers have been exploited in rice [38], wheat [39], maize [40, 41], and barley [42, 43]. However, M“S has achieved the desired goals in coton with limited success due to a genetic botleneck through historic domestication and limited polymorphism in cultivar germplasm [44 47]. “bout 145 morphological markers are reported in coton so far, but they have low utility in variety development because of incapability to assemble diverse markers in a genotype [48]. Isozymes produced through allelic variants are considered more authentic but not widely used due to their diferential expression in diferent growth stages. For improving productivity and other key quantitative traits, coton genetic markers have more value than morphological or isozyme markers [48]. DN“ markers have become handy and efective tools for plant breeders because their expression is not necessary for their detection [49]. In order to enhance the beneits through molecular markers, vast developments have been made in omics , which, in turn, allowed the use of these markers in diverse ways for genetic studies instead of using them solely for phylogenetic studies [50]. Obtaining pure DN“ plays a major role for the develop‐ ment of molecular markers in coton [51 53]; genetic analysis has many drawbacks due to the presence of phenolic compounds, which afect quality of DN“ and protein during tissues grinding [51]. Polygenic traits are mostly afected by the climatic conditions and show discrete variability after hybridization. Recombination frequency allows investigators to diferentiate genes on linkage map by relative distance between a generation and their parents. The main hindrance for QTL mapping of agronomic traits is related to a large number of genes involved in phenotypic expression and their interaction with the environment [54]. “s number of genes afects the trait phenotypically, it is desired that more loci should be evaluated for QTL determination, and the screening of individuals should be done at multiple locations/envi‐ ronments to maximize the use of QTLs. M“” uses QTLs to pyramid favorable alleles and break linkage groups for tagging QTLs of interest [55 57]. In recent years, conventional plant breeders started to use M“S for the identiication of traits with high heritability such as disease resistance, as well as the yield of major ield crops [57]. However, yield‐related components have low heritability, which is a major challenge for the utilization of M“S [56, 58]. M“S is being employed for the identiication of transgressive segregants. Transgressive segregation is the production of plants in F2 generation that are superior to both parents for one or more traits. Transgressive breeding aims at improving yield or contributing to yield‐related traits through transgressive segregation [59 61]. Several QTLs have been identiied for seed coton yield, iber quality, plant architecture, resistance to diseases such as bacterial blight and Verticillium wilt [57], resistance to pests like root knot nematode, and lowering date [62] as well as for abiotic stresses (drought, salt tolerance) [55, 63]. There is a gap between discovery of useful genes and QTLs, and their utilization in breeding programs. To date, few examples are reported [55, 63] for the successful release of genotypes developed by M“S, and they have shown signiicant contribution to yield improvement. High‐ throughput, high‐density genome‐proiling tools enable the rapid and low‐cost of crop Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 genome in a precise and high‐resolution manner. Identiication of molecular variants in DN“ sequence opens opportunities for plant scientists [55]. The potential exists in plant breeding for eicient use of next‐generation sequencing (NGS) that also has revolutionized the plant genomics [55]. Markers can be analyzed across the genomes simply and accurately, with high‐ throughput. Increased number of next generation sequencing allows conducting genome‐wide association studies (GW“S) [63]. It is thanks to the developments in knowledge of useful genetic diversity and QTLs, advances in sequencing, genotyping, and bioinformatics ap‐ proaches that rapid, high‐throughput molecular marker discovery methods have been enabled. Day‐by‐day developments of new, speciic markers, and trait determination tools makes molecular markers important in understanding the genomic variability and diversity within and among species. In this chapter, we discuss about the applications and types of molecular markers, next‐generation sequencing, and role of molecular breeding in development of plants with improved economical traits in coton. . Breeding for polygenic traits Economically important traits such as nutritive value, earliness, agronomic traits, resistance etc. can be improved through M“S [64, 65]. Polygenic mapping allows breeders to estimate and assess the hereditary patern of the traits governed by many genes found throughout genome; Ultimately it leads to eicient utilization of these traits for molecular breeding. Highly saturated genetic maps in a high population index permits to observe the impact of many regions of genomes on a single trait value. Paterson [66] revealed that sharing of homologues during crossing over is the basis of QTLs. The regions of the genomes connected to the traits of economic value are QTLs [67]. “ssociation of a marker s genotypic value to a phenotype is the basis of QTL mapping. Recombination frequency is used to evaluate the relative distance among markers in the linkage map. It is assumed that markers at or lower recombination ratio of 50% are considered as unlinked found either on homologues or alternative loci while the markers which are tightly connected will be transferred to ofspring more often than the unlinked markers [67]. Reinisch et al. [68] developed the pioneer genetic map of coton during 1994. “lthough large number linkage maps have been constructed since then due to abundance of several DN“ markers, it is still needed to determine reliable QTLs from breeding perspective. Yu et al. [69] screened genotypes by simple sequence repeats (SSRs) to map loci connected to iber quality and lint yield in a backcross inbred line and developed a pioneer genetic map using ”IL within allotetraploid cultivated coton species. Map consisted of 392 highly cosegregated loci covering 2895 cM length and having mean interlocus distance 7.4 cM. “s a whole, 39 QTLs were directly connected to yield components and 28 were associated to iber quality. “ltaf et al. [70] explored F2 population developed from three diferent species of Gossypium for identiication of evolutionary relationship among these species by linkage map. Eleven linkage groups were constructed having 521.7 cM map size in coton genome and relative distance of 127 128 Cotton Research 16.8 cM was found among markers through screening randomly ampliied polymorphic DN“s (R“PDs) and ampliied fragment length polymorphisms (“FLPs). Jiang et al. [71] utilized F2 population developed from G. hirsutum × G. barbadense, and produced a restriction fragment length polymorphism (RFLP) genetic map having 3767 cM length; 27 linkage groups with distance of 14.4 cM among loci. Shappley et al. [72] used F2:3 families derived from HS‐46 and M“RC“”UC““G‐1‐8896 genotypes and constructed genetic map by using 120 RFLPs which spanned to 865 cM and arranged in 31 linkage groups. Fifty one linked groups were developed through a map constructed with RFLP and R“PD markers [73] spanning to 6663 cM including 332 “FLPs, 91 R“PDs and three morphological markers. Khan et al. [74] studied comparison for ploidy level to diploid ancestors and tetraploid coton with R“PD markers. 119 F2:3 families developed from MD5678ne × Prema and utilized RFLPs for genetic map. Seventeen linkage panels were distributed on 700.7 cM map having mean distance of 7 8 cM among the markers [75]. RFLP, “FLP, and SSRs were screened in a backcrossed breeding population derived from crosses of [(G. hirsutum cv. Guazunchoz × G. barbadense cv. VH8‐4602) × G. hirsutum cv. Guazunchoz] [76]. Linkage map covered 4400 cM of genome and consist of 888 loci arranged on 26 and 11, long‐ and short‐linkage groups, respectively. EST‐SSRs from G. arboreum were used for linkage map construction in backcross inbred line [(TM1 × Hai7124) × TM1] [77]. Map spans to 5644.3 cM with mean interlocus distance of 9.0 cM. “s a whole, 111 loci were detected with these 99 EST‐SSRs incorporated into backbone map including 511 SSR loci. These EST‐ SSRs will be useful in M“S for improving iber quality. Mei et al. [78] developed interspeciic population among G. hirsutum L. cv. “cala‐44 and G. barbadense L. cv. Pima S‐7 and published genetic map, which covers 3287 cM of the genome. They used “FLPs, RFLPs, and SSRs and have; identiied total 392 loci being 333, 12, and 47 markers, respectively. They were able to identify high repetitive DN“ and heterochromatin in D‐genome and relative distance among mapped loci in “‐genomes that were also compared to homologous in D‐genome [79]. Two hundred and thirty‐three linked loci were mapped in backcross population of [G. hirsutum cv. Guazunchoz × G. barbadense VH8‐4602) × G. hirsutum cv. Guazunchoz] by using 204 SSR markers, which produced 261 polymorphic bands [80]. Linkage map was published by adding 233 loci to already developed map [76] covering 5519 cM genome and having mean inter‐ related marker distance of 4.8 cM and consisting of 1160 loci. Nugyun et al. [80] applied STS markers for developing linkage maps that will fasten the genomics era by using diploid and tetraploid (“tDt) genomes. The genetic map consists of 2584 loci having İnter‐locus marker distance of 1.72 cM and 763 loci intervals depending on 2007 probes from allotetraploid genome while 763 loci at relative marker distance of 1.96 cM intervals identiied by 662 probes in D‐genome. “ll desired homologous chromosome pairs were observed owing to locus repetition. Moreover, number of chromosomal variations including number of inversions and reciprocal translocations were observed. Wang et al. [81] applied microsatellites for identifying QTLs related to iber quality in RIL population. The genetic map was published with two common QTLs for lint percentage and Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 iber length. The results were in accordance to earlier studies and can be utilized in marker‐ assisted breeding. Lin et al. [82], screened SR“P, SSR, and R“PDs, have constructed linkage map, and a mean relevant distance was 9.08 cM among markers and total length of the map was 5141.8 cM. Park et al. [83] published the pioneer linkage map by applying EST‐SSRs in RIL population derived from (G. hirsutum TM1 × G. barbadense Pima) for iber. The linkage having about 27% genome coverage, covering 1277 cM genome and having 193 loci of those 121 newly mapped for iber traits. Researchers [84, 85] have used SSRs and “FLPs for determining oligonucleotides that is a good source for pyramiding of genes for marker‐assisted selection. The mapping population developed by crossing parents having diversity for drought. Highly favorable environment was used; dryland and irrigated regimes for screening of genotypes. Quantitative trait loci mapped on diferent loci including one QTL (”NL1693) for seed coton production on chromosomes 1 and 15 and two additional QTLs (”NL1153 and ”NL2884) on chromosome 6. Moreover, chromosomes 6, 14, and 25 having ”NL2884, ”NL3259, and ”NL1153 marker‐ associated QTLs found for osmotic pressure for drought in highly uniform lines. Researchers also revealed that N“U2715 and N“U2954 can be used as marker for relative water contents while relative water contents with N“U2954 will contribute a lot to drought tolerance in coton. SSRs were analyzed for establishing genetic diversity and QTLs [86]. F2 population of crosses (7235 × TM 1), (HS 427‐10 × TM‐1), and (PD 6992 × SM 3) utilized for assigning QTLs for iber traits in the three diferent linkage maps which span to 666.7, 557.8, and 588 cM, respectively, with number of mapped loci with diference of 86, 56, and 73 [86]. He et al. [87] screened R“PDs, Retrotransposon‐microsatellite amplified polymorphism (REM“P), SSRs, and sequence‐related amplified polymorphisms in hybrids of G. hirsutum L. cv. Handan 208 and G. barbadense L. cv. Pima 90 for construction of linkage map. “s a whole, 1029 loci were mapped on 26 chromosomes; map spans to 5472.3 cM with mean İnter‐locus distance of 5.32 cM. Saleem et al. [85] determined two QTLs related to drought tolerance in F2 progeny developed from diverse parents by applying SSRs and EST‐SSRs. The progeny screened with parents for osmotic pressure using hydroponic culture. “bdurakhmonov et al. [88] revealed that chromosomes 12, 18, 23, and 26 having QTLs controlling lint percentage by applying SSRs and EST‐SSRs in a RIL population. Four QTLs for lint index, eight for seed index, 11 for lint yield, four for seed coton yield, nine for number of seeds per boll, three for iber strength, ive for iber length, and eight for iber ineness were determined in F2 population (G. hirsutum L. cv. Handan 208 × G. barbadense L. cv. Pima 90) [87]. SSRs were used to screen F2 progeny for nematode resistance [89], and researchers identiied gene G”713 that control resistance, and could be used for reniform nematode resistance. They found two QTLs located on chromosome 21 having 168.6 cM on the genetic map while other QTL was located on chromosome 18. Morphological traits of RIL populations developed by hybridization of G. hirsutum and G. barbadense [90]. QTLs governing the plant architecture including plant height, number of primary and secondary branches were screened. Research‐ ers found that angle of branch, angle of fruits, plant height, leaf size, main fruiting, etc. were governed by a single QTL. Infestation of disease is a severe problem in coton, e.g., Xanthomonas 129 130 Cotton Research oxysporum [91], root knot nematode [89, 92 94], Verticillium [57], and coton leaf curl disease (CLCuD) [95, 96] that warn the coton scientist to ind natural resistance sources and their urgent exploitation by using M“S. . DNA makers in coton Several types of molecular markers are available for characterization of germplasm of crop plants (Table ). The amount of variation prevailing in the germplasm helps to maintain genetic conservation [98]. “vailability of vast genomic database provides opportunity to develop enormous markers for detection of genetic variation [99, 100]. “ccording to Weising et al. [101], these molecular markers must be (1) highly polymorphic, (2) codominant, (3) evenly distrib‐ uted in a genome, (4) without pleiotropic efects, (5) easy to handle and fast assayed, (6) low cost and reproducible. The cost of production of a marker is directly related to marker technique in use, polymorphic nature, and eiciency [102]. Polymorphic markers are divided into three types: (1) hybridiza‐ tion‐based, (2) polymerase chain reaction (PCR) based, and (3) DN“ sequence based markers [103]. . . Hybridization‐based markers Hybridization is occurred to the fragments of genomic DN“s produced by restriction endo‐ nucleases with various lengths among individuals. These types of markers are called hybrid‐ ization‐based markers. . . . Restriction fragment length polymorphism Restriction fragment length polymorphism (RFLP) is a type of hybridization‐based marker in plant genome and initially used for detection of polymorphism in a DN“ sequence for gene mapping during the 1975s [31]. Nucleotide sequences of 4, 5, 6, or 8 bp, called restriction sites, are recognized by restriction endonucleases [104]. Digestion of DN“ with restriction enzymes results in fragments whose number and size can vary among individuals, populations, and even within species. Many scientists developed genetic mapping during the 1975s populations of cotons that were analyzed by using RFLP. Domestication of G. hirsutum was investigated with RFLPs [105]; they have revealed that Yucatan is the wild ancestor of upland coton. Wright et al. [106] used RFLP for M“S and evaluated resistance allele for bacterial blight resistance. Hybridization carried out with probes for microsatellite sequences to yield a variable number of tandem repeats (VNTR) and allow oligonucleotide ingerprinting [107]. Joint map was constructed by using F2:3 populations derived from diferent intra‐hirsutum accessions [108]. Two hundred and eighty‐four polymorphic markers and 49 linked pairs were observed on the map. The genetic map spanned to 1502.6 cM having 5.3 cM distance between markers. RFLPs have played a Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 signiicant part for omics studies [109]. Low level of polymorphism, costly chemicals, and more time for analysis limit RFLP use in M“S [104]. S.N. Feature 1 DN“ require (µg) RFLP 10 RAPD 0.02 AFLP 0.5 1.0 SSRs 0.05 SNPs 0.05 2 PCR based No Yes Yes Yes Yes 3 DN“ quality High High Moderate Moderate High 4 No of polymorphic loci analyzed 1 3 1.50 50 20 100 1 3 1 5 Type of polymorphism Single base change, insertion deletion Single base change, insertion deletion Single base change, insertion deletion Change in repeat length Single base change, insertion deletion 6 Dominance Codominant Dominant Dominant/ codominant Codominant Codominant 7 Reproducibility High Unreliable High High High 8 Ease of use and development Not easy Easy Easy Easy Easy 9 “utomation Low Moderate Moderate High High 10 Cost per analysis High Low Moderate Low Low 11 Developmental cost Low Low Moderate High High 12 Need for sequence data Yes No No Yes Yes 13 “ccuracy Very high Very low Medium High Very high 14 Radioactivity detection Usually yes No No No Yes 15 Genomic abundance High Very high Very high Medium Medium 16 Part of genome surveyed Low copy coding regions Whole genome Whole genome Whole genome Whole genome 17 Level of polymorphism Low Low to moderate Low to moderate High High 18 Inheritance Codominant Dominant Dominant Codominant Codominant 19 Detection of alleles Yes No No Yes Yes 20 Utility for genetic mapping Species speciic Cross speciic Cross speciic Species speciic Species speciic 21 Utility in marker‐assisted selection Moderate Low to moderate Low to moderate High Low to moderate 22 Cost and labor involved in generation High Low moderate Low moderate High High Table . Salient features of various molecular markers [97]. 131 132 Cotton Research Ulloa et al. [110] published genetic maps by using intraspeciic populations developed from parents having diverse genetic background. Fifteen linkage groups were used for designating the chromosomes. Earlier mapped data was used for construction of map by observing the deiciency analysis of the probes. QTLs were determined for iber and yield traits by using this map. “s a whole 63 QTLs were found in “ subgenome at ive diferent loci and 29 QTLs observed at 3‐loci of D‐subgenome. First genetic map spans to 117 cM produced 26 QTLs with 54 RFLPs while second map produced 19 QTLs with 27 RFLPs, and spanned to 77.6 cM. It was revealed that these maps will serve as map‐based cloning for iber quality. . . PCR‐based markers PCR‐based markers, i.e., R“PD [111 113], “FLP [114‐116], microsatellites (SSRs) [117‐119], and inter‐simple sequence repeats (ISSRs) [120‐121] represent major class of markers in coton genomics due to their high utility and exploitation. ”elow are the major advantages of PCR techniques as compared to hybridization‐based methods: (1) low amount of DN“ used for genotyping; (2) capacity to amplify fragments from frozen cells; (3) high polymorphism that enables to generate many genetic markers within a short time; and (4) ability to screen many genes simultaneously either for direct collection of data or provide opportunity to collect information prior to submit for nucleotide sequencing [109]. The comparison of diferent aspects of generally used molecular markers is given in (Table ) and brief description of these three classes of molecular markers is described below with reference to coton genetics. . . . Ampliied fragment length polymorphism “mpliied fragment length polymorphism (“FLP) relies on the restricted sequences and PCR ampliication. Initially, genomic DN“ is digested by a restriction enzyme and resulting fragments are ligated with adapters to both ends. Then, the adapter and restriction site sequences are selectively ampliied; only the fragments whose ends are complementary to 3 ends of selective primers are ampliied resulting in small sequences. Finally, a gel is run for the separation of ampliied fragments and it is visualized by luorescence [34]. The focal point of this methodology relies on the magniication of endonuclease restricted fragments through PCR. The important advantages of using of “FLP markers is that they exist in large numbers in genomes, they have a great reproducibility due to high PCR annealing temperatures, and less cost per marker basis [104]. In addition to reliability and reproducibility [116], there is no need of DN“ sequence for analysis. In contrast to RFLPs and microsatellites, enormous polymorphic loci can be investigated by having single oligonucleotide pair running a single gel through “FLPs [122]. For digestion; partially degraded DN“ and good quality DN“ can be utilized, but care should be taken that isolated genomic DN“ should be free of chemicals that interferes with polymerase chain reaction. Lacape et al. [97] initially developed RILs population by introgression of Guazuncho 2 (G. hirsutum) and VH8‐4602 (G. barbadense), and constructed a genetic map with 800 markers Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 (“FLP, RFLP, and SSR) loci. “FLPs and R“PDs were used for development of linkage map in coton [123]. Three hundred and seven SSR markers and 72 “FLP oligonucleotides were used for the development of genetic map in F2 population which derived from intra‐hirsutum hybridization. The map consisted of 27 linkage groups and it has 21, 72 cM distance between the markers [114]. Map saturation in various genotypes of cotons was analyzed [115]. “FLPs were screened in a backcross population developed from intra‐hirsutum cultivars for agronomic traits and iber quality enhancement [124]. They found 50 “FLPs associated with the iber quality traits and few for other; further evaluated that E1M1‐106, E1M4‐153; E1M3‐ 168, E6M3‐266 for lint yield and lint percentage, respectively can be used in future for M“S [124]. “FLPs were used for introgression among G. hirsutum and G. tomentosum being close relative to Upland coton [125]. Through analysis, species‐speciic [11, 16] “FLP markers were selected from G. hirsutum and G. tomentosum, respectively for assessing G. hirsutum relatedness. These species‐speciic “FLP markers would be useful for detecting gene low between G. hirsutum and G. tomentosum. Jixang et al. [124] revealed genetic diversity in a germplasm by using “FLPs. “ range of 0.1 0.34 estimates of genetic diversity were found among the genotypes, and showed that genotypes having signiicant variation in the gene stock include “U 5367, “cala 1517‐99, and L“ 05307025. . . . Random ampliied polymorphic DNA Randomly ampliied polymorphic DN“ (R“PD) relies on use of short and random primers to amplify random portions of genome [126]. Such markers have found to be widespread in population genetic studies whose characterizations of genetic diversity and divergence within and among populations are based on assumptions of Hardy‐Weinberg equilibrium and selective neutrality of the markers is employed [127]. Ultimate success of R“PDs is shown in the increase of molecular markers which require small amount of DN“ and no need for sequencing, except of having all prerequisites for PCR conditions [126]. DN“ fragments having sequence of about 10 bp are ampliied with artiicial primers by using PCR [128]. R“PDs are being used vigorously for proiling of genotype of important ield crops, also for mapping for certain traits in addition to biotic and abiotic stresses. For such studies, R“PD primers show polymorphism and should be free from palindromic sequences and should have minimum 40% GC contents in the fragments [113]. Many scientists have explored R“PDs in coton for studying diferent aspects like phylogenetic studies, genetic diversity, and CLCuV disease screening [111, 112, 128]. R‐6592 and U”C607500 [113, 129] male sterility and fertility restorer traits can be improved by using R“PDs. Lan et al. [130] applied R“PDs for mapping fertility genes that is of immense value in coton and tagged fertility restorer gene R‐ 9 which may be utilized for productivity enhancement. Lan et al. [130] conducted phylogenetic studies in coton and argued that this procedure is helpful and reliable for introgression of desirable traits. R“PDs were used in coton for comparing coton cultivars resistance to jassids, mites, and aphids [131]. DN“ inger printing, mapping and genetic diversity has been studied in coton through R“PDs [132 134]. 133 134 Cotton Research Noormohammadi et al. [135] screened F2 population of Upland coton and Opal variety by using 10 homo‐primers and seven hetero‐primers out of 26 R“PDs and found 261 reproducible bands, with an average of 4.18 [261 bands/17 primers = 15 bands/primer] bands per primer and 22% polymorphism for analyzing genetic resemblance in agronomic traits with 45 (Upland) and 80% (Opal) polymorphism, respectively. ”y applying agarose gel, multilocus genotyping can be carried out by staining with ethidium bromide and this facility is available in every lab working on molecular breeding [136]. R“PDs are often laboratory dependent and require immense care to design protocols for geting polymorphism. Several factors have been reported to inluence the reproducibility of R“PD results such as quantity of template DN“, bufers of polymerase, concentration of magnesium chloride, primer to template ratio, annealing temperature, type or source of DN“ polymerase, and brand of thermal cycler [137]. R“PDs also fail to discriminate between homozygotes and heterozygotes and complication of expressing Mendelian ratio of loci [138]. . . . Intersimple sequence repeat Modiications of microsatellites, which utilize microsatellites‐complementary primers, overcome the need for lanking fragment information [139]. Polymorphism is revealed among simple sequence repeat (SSR) markers by using primer (16 25 bp) adjacent to a single SSR and annealing occur at either ends [139]. ISSR utilizes microsatellites as oligonucleotides in a PCR reaction to amplify inter simple sequence repeats for desired DN“. ISSRs utilize SSRs repeats dinucleotide, trinucleotide, and tetranucleotide as oligonucleotide [140]. Usually, ISSR primers have substantial fragments contrary to R“PD primers, enabling elevated annealing tempera‐ ture, which produce highly polymorphic bands as compared to R“PDs [120, 141]. The ampliied products can be separated by agarose and polyacrylamide gel due to longer length ranged from 200 to 2000 bp [139]. ISSR markers have been vastly used in coton improvement, phylogenetic study and for mapping of germplasm [120, 121]. Parkihya et al. [142] studied genetic diversity among coton genotypes by using nine ISSR oligonucleotides and detected 86 bands of which 54 bands exhibited polymorphism of 62.79% having mean of six bands per primer. The PIC ranged from 0.8616 to 0.9090 and genetic similarity ranged from 0.60 to 0.917. Phylogenetic relation was revealed in 21 coton genotypes by using 12 intersimple sequence repeat primers and observed 49.6% reproducibility [143]. Genetic diversity was studied in coton with 10 ISSR and showed 88.5% polymorphism [144]. Liu and Wendel [145] showed that ISSR can be designed with low cost. Genetic diversity observed in genepool comprised of wild species and elite lines through SSRs and ISSR [146]. They observed 173 alleles having mean 3.93 alleles per locus by analyzing 39 SSRs and 5 ISSR markers which produced 89.6% reproducible bands. “mong genotypes variation ranged from 0.04 to 0.58 while in diploid and tetraploid species it was 0.23 0.57%. Similar to R“PD, there may be some fragments with the same mobility originate from non‐homologous regions [120]. Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 . . . Sequence characterized ampliied region R“PDs have more demerits of polymorphism as compared to other PCR‐based markers which are used for analyzing a large number of individuals with low cost. This problem was overcome by using sequence characterized ampliied region. PCR assay uses couple of distinct oligonu‐ cleotides for DN“ sequence at a speciic locus [147]; oligonucleotides might be having a high‐ copy, dispersed fragment within polymorphic loci. “fter sequencing the two ends of the two reproducible DN“ fragments, one can develop two SC“R markers. SC“R 4311920 can be used in M“S program for screening genotypes with iber strength. ”y using SC“R, codominance is produced [148]. These markers have been used in genetic analysis and used for molecular breeding [149, 150]. Extended sequence speciicity of primers in SC“Rs results in higher reproducibility than R“PDs [151]. SC“R is widely used among researchers for mapping studies within closely related species [152]. SC“Rs are more authentic for M“S after conversion of DN“ markers. SC“R markers are cost efective and highly polymorphic which make them suitable to be used for evaluating large number of mapping populations in coton [152]. QTLs for leaf traits were observed [153]. . . . Sequence‐tagged site Oslen et al. [154] developed sequence tag sites (STS) through observing impact of the PCR on human genome research, and argued that single‐copy DN“ sequences of known map location could serve as markers for genetic and physical mapping of genes along the chromosome. STS marker allows the utilization of PCR with speciic primers which produces one oligonucleotide connected to the trait of interest. In order to utilize STS for molecular breeding, RFLP, “FLP, and R“PDs are usually converted into STS [155]. Thus, in a broad sense, STS include the markers such as microsatellites (SSRs), SC“Rs, and ISSRs mentioned above. ”ackcross breeding population was developed [(”416R × “rk8518) × “rk8518] and used for identiication of STS markers related to fertility [155]. Tetraploid and diploid species were involved and artiicial hybrids created by colchiploidy. R“PDs such as U”C1471400, U”C607500, U”C979700, and U”C169800 loci were associat‐ ed to productivity restoration, and it was veriied that U”C607500 is having enormous val‐ ue for pyramiding genes to be used in molecular breeding [129]. Linkage maps were developed by using STS for diploid and tetraploid (“tDt) Gossypium genomes [156]. Genet‐ ic map composed of 763 loci at 1.96 cM (approximately 500 kb) intervals detected by 662 probes (D), and 2584 loci at 1.72 cM (approximately 600 kb) intervals based on 2007 probes (“tDt). Several coton breeders have used STS markers for identiication of male restorer parental lines for hybrid coton [129] who mapped coton genotypes by using backcross inbred lines (”ILs) and RIL populations with informative primers, and detected 21 and 7 polymorphic STS markers in ”ILs and RIL populations, respectively. Twelve STS markers were mapped in ”IL population, and four of them were located along with resistance gene analog‐ampli‐ ied fragment length polymorphism (RG“‐“FLP) markers on the same chromosome. Im‐ 135 136 Cotton Research portantly, two were mapped on chromosome c 4, lanking two main‐efect QTLs, which were previously detected. These STS markers should be useful for high‐throughput geno‐ typing, gene mapping, and M“S for disease resistance including Verticillium wilt resistance in coton. . . . Simple sequence repeats Tandem repeats composed of several to over hundred repeats of one to four nucleotide motifs are found in all eukaryotic genomes. These repeats are designated as (“““C)n, here n represents number of tandem repeats. The lanking sequences of simple sequence repeats (SSRs) are used for the development of oligonucleotides [118]. Tandem repeats induce variability, which evolve polymorphism of diferent size due to slipped strand arise because of mispairing occurs during DN“ replication [118], variation in size of PCR ampliication/ products induce polymorphism which can be separated by electrophoresis. Kinship studies are conducted by employing SSR markers assess the extent of variation [119]. Vos et al. [157] used agarose and polyacrylamide gel for the identiication of SSRs hav‐ ing codominance nature like “FLP. “kkaya et al. [158] stated that genetic mapping is on fast track due to the use of SSRs in self‐pollinated crops where these markers are of great inter‐ est for breeders [159, 160]. SSRs are mostly codominant, and are indeed excellent for study‐ ing of population genetics and mapping [161 163]. The use of luorescent primers in combination with automatic capillary or gel‐based DN“ sequencers has got its way in most advanced laboratories, and SSRs are also shown to be excellent markers for luorescent tech‐ niques, multiplexing and high‐throughput analysis. Derived from trispecies hybridization that can be segregated for natural leaf defoliation trait. This RIL population screened with microsatellite markers, JESPR‐13, JESPR‐153, and JESPR178 tandem repeats were found to be highly associated to leaf defoliation trait value [162]. It was found that JESPR178 is closely linked to this trait in coton. It has an immense importance that gene pyramiding can be accomplished for molecular breeding [164]. QTLs were tagged using SSRs in the nematode resistance RIL population developed via introgres‐ sion from G. barbadense [165]. In that study, a single marker analysis identiied four major QTLs located on chromosomes 3, 4, 11, and 17 were identiied to account for 8.0 12.3% of the phenotypic variance. Fiber length was increased up to 12 20% in coton by using microsatellites in a population derived from interspeciic hybridization and loci were discovered for marker‐assisted selec‐ tion [166]. Twenty‐three chromosomes were analyzed by SSRs and found on an average relative distance of 4.9 cM [167]. Researchers [168 170] have utilized SSR markers for studying genetic diversity in coton and observed limited genetic variations. Reddy et al. [171] used SSR‐ enriched genomic libraries and identiied 300 SSR markers. Multinational Seed Company has reported more than 1200 SSRs [172]. “bdurakhmonov et al. [173] conducted genome‐wide association mapping based on linkage disequilibrium (LD), scanning Upland germplasm consisting of 334 G. hirsutum accessions collected from Uzbek, Latin “merican, and “ustralian ecotypes. Screening under diferent Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 climates and by using mixed linear model involving population kinship and population structure 12 22 SSR markers were associated with iber length, iber strength, iber ineness and six other iber quality traits. Mei et al. [78] have reported 145 SSR polymorphic markers for yield and yield components in coton by screening germplasm of 358 upland coton varieties. Cao et al. [174] assessed genetic stock iber quality and reported 97 polymorphic SSR markers by using LD. ”olek et al. [57] used SSR markers for verticilium resistance in coton by using F2 population; 255 SSRs were screened over bulks constituted by 10 resistant, and 10 susceptible progenies. QTLs were tagged by using 60 polymorphic markers. Genetic map produced 11 linkage groups having 15.17 cM inter‐locus distance and spanning 531 cM. ”ackcross inbred lines used [175] for observing the genetic variation of 446 SSR markers having relative mean distance of 10 cM interspeciic linkage map and also detected 58 QTLs related to iber quality and yield components. ”y using SSRs, genetic markers associated to coton earliness were determined in progeny developed from intra‐hirsutum hybrids [117], and these markers correspond to bud to lower duration and lower to boll period. Earliness in coton can be induced by the introgression of QTLS located near to the SSR markers such as ”NL1044, DPL0209, N“U1004a, N“U 5046, N“U6078, and TM”0481 [117]. F2 progeny was developed within G. hirsutum for utilizing gene pyramiding in marker‐assisted breeding to enhance iber quality and agronomic traits of economical value by using SSRs, SR“Ps, EST‐ SSRs, and SSCP‐SNPs [176]. Economically valuable traits were evaluated through construction of linkage map, segregation patern observed among the traits and 33 QTLs were identiied [176]. Textile industry entirely depends upon iber with good quality. Marker‐assisted selection allows developing a cultivar having good iber quality. There are many SSRs which can be used for fostering the breeding program; for example, lint percentage can be approved by using TM”0471 and MGHES‐31, TM”0366, ”NL3590, ”NL1395, ”NL1672, ”NL1694, JES‐ PER101, JESPR204, N“U3308, ”NL1672, N“U3308; N“U4024 [168, 177 180]. Genetic base can be broadened for span length by using ”NL 1395, DC40182, N“U2980, ”NL2752, N“U2985, N“U1167, N“U1200, N“U2277 [50, 123, 177, 179]. ”NL1122, ”NL1317, ”NL3145, ”NL1521, CIR307, CGR6164, CGR6683, GH454, ”NL3463, JESPER153, DC40182, N“U 1037, SHIN‐0463, TEM”1618, N“U3736, N“U445, N“U780, N“U1102, N“U1197, N“U1322, N“U1369, JESPR218, TMD05 can be applied for iber strength enhancement [52, 92, 173, 174, 176, 181 188]. . . . Single nucleotide polymorphism Single nucleotide polymorphisms (SNPs) manifest alteration in single base. SNPs are the most frequent occurring variability in the individuals which is found in each 1000 bases [189]. These are changes in bases from transitions (C/T or G/“) to transversions (C/G, “/T, C/“, or T/G) while insertions and deletions also induce SNPs which show single base changes. SNPs show useful allelic variations and have been markers of choice in various genetic studies [190]. Rapid progress in high‐through put sequencing has allowed discovering SNPs in complex genomes 137 138 Cotton Research with economic value by using genotyping by sequencing [191]. Frelichowski et al. [167] revealed that reproducibility is a major hindrance for using large number of markers devel‐ oped in G. arboreum, G. raimondii and G. hirsutum [192]. In combination with genome and expressed sequence tags (ESTs) in model plant species [193], the eiciency of Sanger sequenc‐ ing has been improved to accelerate the identiication of variations at single base pair resolu‐ tion [194]. Genotyping in plant sciences is progressing rapidly because SNPs for observing variation in a speciic locus are utilized. Moreover, availability of enormous SNPs due to insertions‐ deletions and whole genome genomic studies is laying the corner stone for next generation sequencing [195]. Developed genomic databases and SNPs information allow evolving SNPs to an inluential research for related relatives. Owing to most common type of DN“ polymor‐ phism, SNPs are also lexible in the selection of SNP variants at target loci, and they provide the option to choose from a large number of genome‐wide loci when selecting sets of infor‐ mative markers for speciic germplasm pools [196]. ”reeding programs comprised of genomic estimated breeding values are highly favored for whole genome techniques additional to targeted loci [197 199]. Economically important traits from breeding perspective are also investigated through genome‐wide sequencing [200], saturated mapping of polygenic traits [201], and by using LD‐ mapping [202]. “n et al. [203] studied the expression of R2R3‐MY” transcription factors where few are expressed during iber initiation and elongation. They observed phylogenetic relation among R2R3‐MY” genes and published a map by using SNPs in Upland coton. QTLs were mapped in population derived from intra‐hirsutum and interspeciic (G. hirsutum × G. barbadense) [204]. Researchers [204] have collected all published QTL data. QTLs were identiied for seed, yield and iber quality by using two populations through meta‐analysis. QTLs connected to biotic and abiotic stressed were also detected. However, the development of high‐throughput genotyping platforms for large numbers (thousands to millions) of SNPs has proved to be relatively time‐consuming and costly. Deynze et al. [205] reported more than 200 loci in G. hirsutum breeding germplasm, which were genetically mapped on mapping population derived from TM‐1 and 3‐79. Genepool comprised of 24‐accessions derived from 8‐parental lines of mapping populations of six cot‐ ton species and16 promising coton strains used for genotyping. “s a whole more than 1000 SNPs were polymorphic among G. hirsutum and G. barbadense were developed from 270 loci and 290 indels from 92 loci. [205]. Roche 454 pyrosequencing platform in four allotetra‐ ploid cotons using reduced representation library (RRL) have helped to map a large num‐ ber of SNPs [206]. The conversion rate of SNPs using K“SPar assay was about 35.8%. Three hundred and sixty‐seven SNP markers were used for linkage map construction, which span‐ ned to 1688 cM. High‐resolution maps can be formed rapidly by utilizing parallel sequenc‐ ing methods to determine the reads in resequencing. Paciic ”iosciences technologies used for long reads [207] while Illumina and Ion Torrent are applied in sequencing for geting short reads [196]. Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 . Mapping populations The group of plants, which is used for screening of molecular markers and segregated for the trait of interest, is designated as mapping population. From commercial point of view, such populations are developed from within species and can be also developed between diferent species for creating desirable variation. Polymorphism is compulsory in the progenitors for required trait [208]. The exchange of chromosome fragments during crossing over produces recombination, which provides the basis for developing linkage maps [59]. Populations are required for creating genetic maps in order to locate the quantitative trait loci from economical point of view. Mapping populations can be exempliied by F2, backcross, recombinant inbred lines (RILs), doubled haploid lines (DHL), F2‐derived F3 (F2:F3) populations, and near‐isogenic lines (NILs). F1 is produced by seling two parents, having extreme properties for trait of interest that show a signiicant polymorphism for whichever type of loci are scored. Mostly, this population is used for genetic mapping as it requires less time for development. However, there are some drawbacks for this population, most important of which is the fact that it is not stable. Qualitative and quantitative traits in coton have been mapped by using F2 [70, 74, 81, 86]. ”ackcross (”C) population is developed by crossing a genotype with an elite cultivar, which is deicient for a single gene or QTL [67]. “ concept of ”C population was developed in 1922 and widely applied in plant breeding programs till 1960 [209]. ”ackcross population has been used for linkage mapping in coton for improving various traits [129, 155 156]. Near isogenic lines(NILs) can be developed either by using seling until purity is “chieved; for all traits with wide variation of the trait of interest among NILs or by hybridizing the donor parent to the F1 plants and choosing the desired trait [63]. NILs are of high importance for genetic studies as they are stable like RILs. Researchers [210] used NILs for observing QTLs related to yield and drought related traits. They evaluated that NILs can be used for evaluating drought and can be used for M“S. Essenberg et al. [116] developed NILs in coton and mapped bacterial blight resistance. They revealed that lines having “cala‐44 in their parentage are showing dominance to bacterial blight. Recombinant inbred lines (RIL) are stable and are developed by using single seed descent method from irst ilial generation. It continues until homozygosity is obtained in the individ‐ uals. RILs are permanent and can be screened at multiple locations for desired traits. Each strain is homozygous and stable in the RIL population. Each cycle of seling results in enhanced recombination frequency and these populations are highly suitable for saturated mapping [129]. Moreover, for genetic mapping in coton this population has been utilized for various traits including nematode resistance [165], iber quality improvement [166], and verticilium resistance [175]. One of the drawbacks of this population is long duration for development in which segregation bias can occur due to removal of some genotypes after seling. “nother disadvantage of using these populations is that major QTLs are having a masking efect, and multiple QTLs are having epistatic efects. 139 140 Cotton Research Nested association mapping (N“M) [188] is designed for precise identiication of QTLs [177]. Economically valued traits related to yield and subsequently to textile sector can be eiciently studied through developing new populations like N“M. N“M populations potentially address the limitations of conventional mapping populations . Some applications of markers in breeding schemes . . Marker‐assisted backcrossing The simplest, most widely used, and the most eicient form of M“S is M“”. In this form, two parents are used for the development; one is donor parent having trait of interest for transferring the targeted gene/loci and the other is recipient parent which is lacking gene. Parents are hybridized and F1 is developed. Marker‐assisted backcrossing relies upon the presence of a molecular marker associated with the trait, instead of targeting the expression of phenotypic value in traditional breeding. F1 is planted for conirming the marker loci at initial stages of development, and pure F1 is hybridized to recurrent parent. Markers are evaluated among individuals at the initial development stages of ”CF1 and hybridized to recurrent parent having alternative alleles. ”C1 individuals show segregation frequency of F1 population gametes as two genotypes are involved in this population. Highly eicient map is constructed by using this population in contrast to F2 population. This population is mostly used for overcoming hybrid in viability and hybrid breakdown in interspeciic crosses [129]. This process is continued until three to four ilial generation for stabilizing the marker and its associated trait of interest. M“” population has been utilized for observing traits of interest through quantitative trait loci [115]. . . Pedigree selection ”reeding techniques within the two cultivated tetraploid species rely on crossing and selection of traits using pedigree and recurrent selection methods. Promising genotypes having desirable traits can be developed using M“S and can be combined into a pedigree‐based selection. Mostly, the eiciency of M“S was investigated using two populations from pedigree selection, and modiied backcrossing pyramiding has been developed [211]. The selection eiciency for the iber strength was greatly increased when QTLfs‐1 was selected simultane‐ ously with two molecular markers with known genetic distance [211]. . . Marker‐assisted recurrent selection MARS Molecular markers should be applied for plant improvement in conjunction with the latest breeding methodologies. Marker‐assisted recurrent selection ofers an opportunity to get maximum output from a recurrent selection [212]; and it is used for introgression of multiple genes. Quantitative traits can be enhanced eiciently by using M“RS, which allows seling and genotyping within same cropping season in one cycle of selection. The increase in genetic Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 gain was doubled from M“RS in some populations as compared to phenotypic selection [213]. In coton, resistance to “merican bollworm was achieved by using marker‐assisted recurrent selection; they revealed highly signiicant diferences in individuals studied by M“RS for this insect resistance [214]. . Gene pyramiding for MAS Gene pyramiding has been widely used for combining number of genes especially disease resistance genes for speciic races of a pathogen. Vertical resistance for diferent strains of pathogens is done by involving multiple strains. It is also done by molecular breeding because breeding for resistance is extremely diicult to achieve using conventional methods. Gutiérrez et al. [215] have used this technique for nematode resistance in coton while [155] they applied sequence tag sites and screened STS markers associated with fertility restoring genes in coton. . Next‐generation sequencing NGS SNP genotyping with latest high‐throughput sequencing has the potential to speed up the breeding programs [216]. New DN“ sequencing technologies have made it possible for the breeders and investigators to perform a genome analysis not only more rapidly but also less expensively [179]. High‐throughput bioinformatics assist to identify large number of nucleo‐ tides per run [217]. Researchers have developed a lot of NGS methods with success in diverse platforms, which include Roche 454 FLX Titanium [218 220], Illumina MiSeq and HiSeq2500 [221], Ion Torrent PGM [222]. Genomic research contributes immensely to plant and animal sciences thanks to the advances in sequencing techniques [180, 221, 223 228]. The ultimate aim of all these techniques is to discover an authentic marker that could be used for sequencing in M“S with economical beneits [229 230]. Polyploidy is the main hindrance for isolation of useful SNPs in coton because it produces homeologous and paralogous sequence variants which are combined together in allelic variations among cultivars [231 232]. Two cultivated tetraploids species were screened for the development of genomic SNPs through NGS by using reduced representation library obtained from Roche 454 pyrosequencing [206]. Competitive allele‐speciic PCR (K“SPar) showed 35.8% validity of SNPs and developed the genetic map of G. hirsutm via 367 SNP markers which spanned to 1688 cM. Gore et al. [233] developed a linkage map in a RIL population derived from intra‐hirsutum cv. TM‐1, and NM24016. The genetic map covered about 50% of the G. hirsutum genome which consisted of 429 SSRs and 412 SNPs. They also tagged 10 QTLs related to iber quality, which provided a unique resource for mapping. ”efore “fymetrix became commercially available, Gene Chip coton genome array consisting of 239,777 probe sets that represent 21,485 coton transcripts has been developed [234, 235]. Sequences from Genome database, dbEST and 141 142 Cotton Research RefSeq were used for the development of Chip which promises to be an excellent source for genomics. . Genotyping by sequencing In agricultural sciences, the discovery of reliable and true SNPs is compulsory for knowing about the utilization and importance of particular sequences. Molecular breeding tools can be applied to explore germplasm without available genomic data through genotyping by sequencing (G”S) methodology. G”S permits researchers to analyze complex genomes of polyploid species eiciently at low cost and it has been widely used due to the latest devel‐ opments in high‐throughput sequencing [191]. Reduced representative libraries are developed by using endonucleases [55, 178, 236]. Single nucleotide polymorphism is discovered for genomic studies [237]. Genomic techniques; genome‐wide association study (GW“S), genomic diversity, genetic linkage analysis, molecular marker discovery ofer to screen genotypes upon genotypic basis for traits of interest through G”S. Genotyping and reproducibility of markers are performed in a single step through G”S and SNPs are developed [238]. G”S‐based sequencing data are used for developing genetic map and tagging markers with quantitative traits in populations derived from diferent ways, i.e., ilial generations, RILs, etc. and germplasm collections [218]. G”S approach has been used eiciently for genetic analysis and marker development of rapeseed, lupin, letuce, switchgrass, soybean, maize, and coton [38, 219, 222 224, 233, 239]. The merits of G”S over existing marker development methodologies include availability of large number of markers, fast screening of populations composed of more number of indi‐ viduals, diverse genotyping systems to tackle multiple traits, and more precise SNPs discovery and validity due to availability of high‐throughput sequencing data [216]. Recently, G”S approach has been used to identify SNPs in the collections of RILs of wheat and to map various traits useful for breeding programs [55]. It is needed that eforts should be made to develop strategies for geting the beneits of NGS and advanced genotyping from breeder perspectives [196]. G”S protocol of Poland et al. [236] likely is needed to maximize the cost‐efective concurrent discovery and genotyping of SNPs within coton populations. “lthough very eicient and productive in terms of achieving the desired goals, there are some drawbacks in G”S as well. G”S has incapability to assign true alleles of each locus in polyploids as compared to other techniques. “s exempliied, Huang et al. [178] used RILs and biparental populations for assessing the utility of G”S in hexaploid oat. They observed that data analysis algorithm factors involved in SNP discovery, developed G”S derived loci description by forming two bioinformatics worklow. Its genetic map spans to 45,117 loci, which will be a source of further genetic studies [178]. Islam et al. [240] used G”S with two diferent approaches in cultivated coton germplasm consisting of 11 diverse cultivars and their random‐mated RILs. “uthors have discovered a large set of polymorphic SNPs with broad applicability. They identiied 4441 and 1176 Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 polymorphic SNPs with minor allele frequency of ≥0.1. The utility of developed SNP markers were conirmed using SNPs in 154 Upland coton accessions with high genetic diversity. . Association mapping Genome‐wide association study is used for developing highly saturated maps in coton germplasm [241]. This technique allows detecting association among various markers and traits through assessing of the genetic diversity of required traits [242]. Linkage disequilibrium‐ based mapping (LD‐mapping) is the advanced tool to study complex traits governed by many genes. LD‐mapping has been successfully used in self‐pollinated plants [243]. Microsatellites were screened in germplasm consisting of varieties at diferent locations to tag yield and iber quality QTLs [202]. QTLs mapped for yield and iber quality traits will serve as a reliable source to determine the diversity within the species and will contribute a lot in M“S [202]. In contrast to biparental populations, association mapping fosters molecular breeding because a vast genetic diversity is present in germplasms due to diverse sources [173]. Several protocols have been developed including complexity reduction of polymorphic sequences (CRoPS) [244], restriction site associated DN“ (R“D) [216], G”S [195], and sequence‐based genotyping (S”G) [245, 246] for genome analysis. Of all protocols, LD‐mapping is on the top thanks to innovations done for high resolution. “ssociation mapping is an authentic way for molecular tagging as it allows the screening of quantitative traits of value in a precise way [247]. Genome‐ wide association makes it possible to detect association among various markers and traits. “bdurakhmonov et al. [46] used LD‐mapping in a germplasm collection, which included photoperiodic lines. Simple sequence repeats were used for assessing the extent of LD in coton and the major iber quality QTLs were tagged using mixed linear model. Nested association mapping is also being used for identiication of suitable SSRs in a N“M population derived from 20 diverse genotypes of G. hirsutum with Namangan‐77. SSR marker screening for development of highly saturated map through N“M F2:3 populations for traits of immense value in coton is underway [188]. . Public data resources Sequenced genomic information allows breeders to analyze the genetic variation [248]. Major databases, which serve as a foundation, include CotonGen [58], Comparative Evolutionary Genomics of Coton [249], National Center for ”iotechnology Information [250] for Express sequence tags resource, TropGENE Database [251], the Coton Diversity Database [252] and ”“CMan resources at Plant Genome Mapping Laboratory [253]. These resources provide genomic and heredity data of the coton germplasm, QTLs tagged to loci and highly saturated linkage maps. 143 144 Cotton Research . Targeting‐induced local lesions in genomes TILLINGS Phenotypic variation in plant genomes is produced by variation in DN“ bases, which can be induced naturally and/or using diferent chemicals [254]. The targeting‐induced local lesions in genomes (TILLING) technique allows determining an allelic variation precisely in a single‐ base pair for the targeted gene. Chemical treatments have been applied to generate SNP mutations. Point mutations, which are useful from breeder s perspective, can be detected by TILLING and ECOTILLING techniques [255]. The mutagens used for induction of point mutation are highly selective and optimal concentration can spontaneously produce single base alternations at a high frequency in TILLING. Knock‐out population is developed by treating the seed with chemicals, inducing change in DN“ sequence [256]. “uld et al. [257] used TILLING in G. arboreum and demonstrated the applicability of this technique in coton. The ultimate success to produce large number of sequence variations of target genome depends upon duration of application, relative capability of ethyl methane sulfonate (EMS), and γ‐rays [53]. “slam et al. [53] screened three Gossypium sp. (G. hirsutum, G. barbadense and G. arboreum) and constructed a kill curve. They observed the impact of diferent mutagens (EMS and γ‐rays) consisting of eight diferent concentrations of EMS (0.1 0.8%) and two levels of γ‐rays (100 800 Gy). The genotypes of each species were evaluated with morphological parameters emergence and plant height, and yield traits (number of bolls per plant, boll weight, lint yield and lint percentage). For reverse and forward genetics point of view, viable accessions were selected from mutagenized genotypes. They revealed that EMS showed signiicantly high mutation rate than γ‐rays. There are many software tools which help to observe the bases variation; for instance, the method that determines whether a change occurs in an amino acid hampering codon is named conservation‐based SIFT (sorting intolerant from tolerant) [258]. Taylor [259] described that any alternation of a gene can be detected by P“RSESNP (for Project “ligned Related Sequences and Evaluate SNPs [260]; graphs show the changes in sequence by using precise co‐segregating information, positioning of coding/and noncoding regions and reference DN“ sequence. . Conclusions Developing reliable markers, which will work in diferent populations and utilized in the breeding to enhance selection eiciency, is a very important step for breeding. Markers should allow desired genotype selection because of their tight linkage to the trait of interest. On the other hand, emerging technologies like high‐throughput marker systems and marker‐based selection methodologies have been developed, and are currently being used eiciently in coton breeding. It is also promising that some economically important traits like iber quality, yield, Verticillium wilt resistance, coton leaf curl virus, drought tolerance, nematode resistance can be enhanced by using M“S. Genetic diversity can also be evaluated by using DN“ markers before starting breeding program. Tremendous eforts have been carried for studying genetic diversity from genotypic and phenotypic aspects in germplasm accessions of coton. Many Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 QTLs related to economical traits have been discovered. It is an emerging concern that eforts should be made for the utilization of molecular breeding methodologies to enhance coton productivity, which can be enhanced through the recent developments in NGS. Moreover, highly saturated maps are useful for determining genetic manipulations from heredity perspectives, and SNPs are the best for this purpose. These markers along with QTLs provide innovative tools in the coton genomics era. Author details Yuksel ”olek1, Khezir Hayat1, “dem ”ardak1* and Muhammad Tehseen “zhar2 *“ddress all correspondence to: [email protected] 1 Faculty of “griculture, “gricultural ”iotechnology Department, Kahramanmaras Sutcu Imam University, Kahramanmaras, Turkey 2 Department of Plant ”reeding and Genetics, University of “griculture, Faisalabad, Paki‐ stan References [1] Edwards MD, Stuber CW, Wendel JF. Molecular‐marker‐facilitated investigations of quantitative‐trait loci in maize. I. Numbers, genomic distribution and types of gene action. Genetics, 1987; 116: 113 125. PMCID: 1203110. [2] Van Esbroeck G“, ”owman DT, Calhoun DS, May OL. Changes in the genetic diversity of coton in the U.S. from 1970 to 1995. Crop Science, 1998; 38: 33 37. DOI: 10.2135/ cropsci1998.0011183X003800010006x. [3] Collins NC, Tardieu F, Tuberosa R. Quantitative trait loci and crop performance under abiotic stress: where do we stand? Plant Physiology, 2008; 147: 469 486. DOI: www.plantphysiology.org/cgi/doi/10.1104/pp.108.118117. [4] Collard CY”, Mackill JD. Marker‐assisted selection. “n approach for precision plant breeding in the twenty‐irst century. Philosophical Transactions of the Royal Society ”: ”iological Sciences, 2008; 363: 557 572. DOI: 10.1098/rstb.2007.2170. [5] ”udak H, ”olek Y, Dokuyucu T, “kkaya V“. Potential uses of molecular markers in crop improvement. KSÜ Fen ve M(hendislik Dergisi. 2004; 7: 75 79. [6] Kalivas “, Xanthopoulos F, Kehagia O, Tsaftaris “S. “gronomic characterization, genetic diversity and association analysis of coton cultivars using simple sequence 145 146 Cotton Research repeat molecular markers. Genetics and Molecular Research, 2011; 10: 208 217. DOI: 10.4238/vol10‐1gmr998. [7] Zhang Y, Lin Z, Li W, Tu L, Nie Y, Zhang X. Studies of new EST‐SSRs derived from Gossypium barbadense. Chinese Science ”ulletin, 2007; 51, 2522 2531. DOI: 10.1007/ s11434‐007‐0399‐2. [8] “vailable from: htp://www.textileworld.com/textile‐world/iber‐world/2015/10/icac‐ stable‐world‐coton‐trade‐expected‐in‐2015‐16/ [18‐03‐2016]. [9] Fryxell P“. “ revised taxonomic interpretation of Gossypium L. (Malvaceae), Rheedea, 1992; 2: 108 165. [10] ”easley JO. The production of polyploids in Gossypium. Journal of Heredity, 1940; 31: 39 48. [11] Endrizzi J. Turcote EL, Kohel RJ. Genetics, cytology and evolution of Gossypium. “dvances in Genetics, 1985; 23: 271 375. [12] Ortiz R. ”iotechnology with horticultural and agronomic crops in “frica. “cta Horti‐ culture. 2004; 642: 4356. [13] Kumar LS. DN“ markers in plant improvement: an overview. ”iotechnology “dvan‐ ces, 1999; 17: 143 182. DOI: 10.1016/S0734‐9750(98)00018‐4. [14] King RC, Stansield WD. “ Dictionary of Genetics. 4th ed. New York: Oxford University Press; 1990. p. 188. [15] Schulmann “H. Molecular markers to assess genetic diversity. Euphytica, 2007; 158: 313 321. DOI: 10.1007/s10681‐006‐9282‐5. [16] Joshi C, Nguyen H. R“PD (random ampliied polymorphic DN“) analysis based inter varietal genetic relationships among hexaploid wheats. Plant Science, 1993; 93: 95 103. .DOI: 10.1016/0168‐9452(93)90038‐2. [17] Winter P, Kahl G. Molecular marker technologies for plant improvement. World Journal of Microbiology & ”iotechnology, 1995; 11: 438 448. DOI: 10.1007/”F00364619. [18] Jones CJ, Edwaeds KJ, Castaglione S, Winield MO, Sela F, Van De Weil C, ”redemeijer G, Vosman ”, Mathes M, Daly “, ”retschneider R, ”etni P, ”uiti M, Maestri E, Malcevschi “, Marmiroli N, “ert R, Volckaert G, Rueda J, Linacero R, Vazquez “, Karp “. Reproducibility testing of R“PD, “FLP and SSR markers in plants by a network of European laboratories. Molecular ”reeding. 1997; 3: 381 390. DOI: 10.1023/“: 1009612517139. [19] Gupta PK, ”alyan HS, Sharma PC, Ramesh ”. Microsatellites in plants: a new class of molecular markers. Current Science, 1996; 70: 45 53. [20] Roychowdhury R, Taoutaou “, Hakeem KR, Gawwad MR“, Tah J. Molecular marker‐ assisted technologies for crop improvement. In: Roychowdhury R, editor. Crop Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 Improvement in the Era of Climate Change. International Publishing House, India DOI: 10.13140/RG.2.1.2822.2560. [21] Thotappilly G, Magonouna HD, Omitogun OG. The use of DN“ markers for rapid improvement of crops in “frica. “frican Crop Science Journal. 2000; 8: 99 108. [22] “ken JV. Marker‐“ssisted Selection: “ Noninvasive ”iotechnology “lternative to Genetic Engineering of Plant Varieties. “Z “msterdam, The Netherlands: Greenpeace International Otho Heldringstraat; 2009. [23] Mohan M, Nair S, ”hagwat “, Krishna TG, Yano M, ”hatia CR, Sasaki T. Genome mapping, molecular markers and marker‐assisted selection in crop plants. Molecular ”reeding, 2012; : 87 103. DOI: 10.1023/“:1009651919792. [24] Francia E, Tacconi G, Crosati C, ”arabaschi D, ”ulgarelli D, Dall “E, Vale G. Marker‐ assisted selection in crop plants. Plant Cell and Tissue Organ Culture, 2005; 82: 317 342. DOI: 10.1007/s11240‐005‐2387‐z. [25] ”rumlop, Sarah, Finckh MR. “pplications and potentials of marker‐assisted selection (M“S) in plant breeding. Federal “gency for Nature Conservation Konstantinstrasse ”onn, Germany ”undesamt f(r Naturschuz (”fN); 2010. p. 31. URL: htp:// www.bfn.de. [26] Crouch JH, Ortiz R. “pplied genomics in the improvement of crops grown in “frica. “frican Journal of ”iotechnology, 2004; 3: 489 496. DOI: 10.5897/“J”2004.000‐2099. [27] Hayashi K, Yoshida H, “shikawa I. Development of PCR‐based SNP markers for rice blast resistance genes at the Piz locus. Theoretical and “pplied Genetics, 2004; 108: 1212 1280. DOI: 10.1007/s00122‐003‐1553‐0. [28] Jain SM, ”rar DS, “hloowalia ”S. Molecular Techniques in Crop Improvement. 2nd ed. Dordrecht, The Netherlands: Kluwer “cademic Publishers: 2002. p. 772. [29] Kumpatla SP, ”uyyarapu R, “bdurakhmonov IY, Mammadov J“. In: Ibrokhim IY, editor. Genomics‐“ssisted Plant ”reeding in the 21st Century: Technological “dvances and Progress. Croatia: In Tech. Plant ”reeding; 2012;. [30] Gupta PK, Kumar J, Mir RR, Kumar “. Marker‐assisted selection as a component of conventional plant breeding. Plant ”reeding Reviews, 2010; 33, 145 217. [31] Helentjaris T, Slocum M, Wright S, Schaefer “, Nienhuis J. Construction of genetic linkage maps in maize and tomato using restriction fragment length polymorphisms. Theoretical and “pplied Genetics, 1986; 61: 650 658. DOI: htp://dx.doi.org/ 10.1155/2014/607091. [32] Welsh J, McClelland M. Fingerprinting genomes using PCR with arbitrary primers. Nucleic “cids Research, 1990; 18: 7213 7218. [33] Vos P, Hogers R, ”leeker M, Reijans M, Van DLT, Hornes M et al. “FLP: a new technique for DN“ ingerprinting. Nucleic “cids Research, 1995; 23: 4407 4414. 147 148 Cotton Research [34] Semagn K, ”jornstad “, Ndjiondjop MN. “n overview of molecular marker methods for plants. “frican Journal of ”iotechnology, 2006; 5, 2540 256. [35] Lam HM, Xu X, Liu X, Chen W, Yang G, Wong FL, et al. Resequencing of 31 wild and cultivated soybean genomes identiies paterns of genetic diversity and selection. Nature Genetics, 2010; 42: 1053 1059. DOI:10.1038/ng.715. [36] Singh H, Deshmukh RK, Singh “, Singh “K, Gaikwad K. Highly variable SSR markers suitable for rice genotyping using agarose gels. Molecular ”reeding, 2010; 25: 359 364. DOI: 10.1007/s11032‐009‐9328. [37] Sonah H, Deshmukh RK, Singh VP, Gupta DK, Singh NK, Sharma TR. Genomic resources in horticultural crops: status, utility and challenges. ”iotechnology “dvances, 2011; 29, 199 209. DOI: 10.1016/j.biotechadv.2010.11.002. [38] Conaway C, Cartinhour S, “yres N, McClung “M, Lai XH, Marcheti M“, Park WD. PCR based markers linked to blast resistance genes in rice. In: Proceedings of the 27th Rice Technical Working Group Meeting, Reno‐Sparks, NV, US“, 1 4 March 1998. p. 77. [39] Koebner RMD, Summers RW. 21st century wheat breeding: plot selection or plate detection? Trends in ”iotechnology, 2003; 21: 59 63. DOI: 10.1016/S0167‐7799(02)00036‐ 7. [40] Stuber CW, Polacco M, Senior ML. Synergy of empirical breeding, marker‐assisted selection, and genomics to increase crop yield potential. Crop Science, 1999; 39: 1571 1583. DOI: 10.2135/cropsci1999.3961571x. [41] Tuberosa R, Salvi S, Sanguineti MC, Maccaferri M, Giuliani S, Landi P. Searching for QTLs controlling root traits in maize: a critical appraisal. Plant and Soil, 2003; 255: 35 54. DOI: 10.1023/“:1026146615248. [42] Thomas W. Prospects for molecular breeding of barley. “nnals of “pplied ”iology, 2003; 142: 1 12. DOI: 10.1111/j.1744‐7348.2003.tb00223.x. [43] Williams KJ. The molecular genetics of disease resistance in barley. “ustralian Journal of “gricultural Research 2003; 54: 1065 1079. DOI: 10.1071/“R02219. 0004‐ 9409/03/111065. [44] Iqbal MJ, Reddy OUK, El‐Zik KM, Pepper “E. “ genetic botleneck in the evolution under domestication of upland coton Gossypium hirsutum L. examined using DN“ ingerprinting. Theoretical and “pplied Genetics, 2001; 103: 547 554. DOI: 10.1007/ PL00002908. [45] Rahman M, “sif M, Ullah I, Malik K“, Zafar Y. Overview of coton genomic studies in Pakistan. Plant & “nimal Genome Conference XIII. San Diego, 2005, C“, US“. [46] “bdurakhmonov IY, Kohel RJ, Yu JZ, Pepper “E, “bdullaev ““, Kushanov FN, Salakhutdinov I”, ”uriev ZT, Saha S, Scheler ”E, Jenkins JN, “bdukarimov “. Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 Molecular diversity and association mapping of ibre quality traits in exotic G. hirsutum L. germplasm. Genomics, 2008; 92: 478 487. DOI: 10.1016/j.ygeno.2008.07.013. [47] Zehr U”, editor, Coton, ”iotechnology in “griculture and Forestry. Heidelberg: Springer‐Verlag; 2012. DOI: 10.1007/978‐3‐642‐04796‐1_5. [48] Percy RG, Kohel RJ. Qualitative genetics. In: Smith CW, Cothren JT, editors. Coton. Origin, History, Technology, and Production. New York: John Wiley & Sons; 1999. p. 319 360. [49] “rshad M, Sajjad H. Molecular marker technology for coton plant improvement. IC“C, 2002; March 8 13. [50] Joshi SP, Prabhakar K, Ranjekar PK, Gupta VS. Molecular markers in plant genome analysis. htp/www.ias.ac.in/currsci/jul25/articles 15.htm; 2011. p. 1 19. [51] Saha S, Karaca M, Jenkins JN, Zipf “E, Reddy UK, Kantey RV. Simple sequence repeats as useful resources to study transcribed genes of coton. Euphytica, 2003; 130: 355 364. 51. DOI: 10.1023/“:1023077209170. [52] Sun FD, Zhang JH, Wang SF, Gong WK, Shi YZ, Liu “Y, Li JW, Gong JW, Shang HH, Yuan YL. QTL mapping for iber quality traits across multiple generations and environments in upland coton. Molecular ”reeding, 2012; 30: 569 582. DOI: 10.1007/ s11032‐011‐9645‐z. [53] “slam U, Khan ““, Cheema HMN, F. Imtiaz, Malik W. Kill curve analysis and response of ethyl methanesulfonate and γ‐rays in diploid and tetraploid coton. International Journal of “gricultural and ”iological Engineering, 2013; 15: 11 18. DOI: 12 724/2013/15 1 11 18. [54] Lee M. DN“ markers and plant breeding programs. “dvances in “gronomy, 1995; 55: 265 344. DOI: 10.1016/s0065‐2113(08)60542‐8. [55] Elshire RJ, Glaubiz JC, Sun Q, Poland J“, Kawamoto K, ”uckler ES, Mitchell SE. “ robust, simple genotyping‐by‐sequencing (G”S) approach for high diversity species. PLoS One 2011; 6: e19379. DOI: 10.1371/journal.pone.0019379. [56] Ribaut JM, Hoisington D. Marker‐assisted selection: new tools and strategies. Trends in Plant Science, 1998; 3: 236 238. [57] ”olek Y, El‐Zik KM, Pepper “E, ”ell ““, Magill CW, Thaxton PM, Reddy OK. Map‐ ping of Verticillium wilt resistance genes in coton. Plant Science, 2005; 168: 1581 1590. DOI: 10.1016/j.plantsci.2005.02.008. [58] CotonGeN [internet]. 2016. “vailable from: htps://www.cotongen.org. [“ccessed 2016‐03‐08] [59] Tanksley SD, Young ND, Paterson “H, ”onierbale MW. RFLP mapping in plant breeding: new tools for an old science. ”iotechnology, 1989; 7: 257 264. DOI: 10.1038/ nbt0389‐257. 149 150 Cotton Research [60] Paterson “H. Molecular Dissection of Complex Traits. CRC Press (Taylor & Francis Group) UK; 1997. IS”N 9780849376863. C“T# 7686. [61] “bdurakhmonov IY, ”uriev ZT, Shermatov SE, et al. Marker‐assisted selection for complex iber traits in coton. 5th World Coton Research Conference, Special session of ICGI, Mumbai, India; 2011, 7 12 November 2011. [62] Voss‐Fels K, Snowdon RJ. Understanding and utilizing crop genome diversity via high‐ resolution genotyping. Plant ”iotechnology, Journal, 2015. DOI: 10.1111/pbi.12456. [63] Wang S, Chen† J, Zhang W, Hu Y, Chang L, Fang L, Wang Q, Lv F, Wu H, Si H, et al. Sequence‐based ultra‐dense genetic and physical maps reveal structural variations of allopolyploid coton genomes. Genome ”iology, 2015; 16: 108. DOI: 10.1186/s13059‐015‐ 0678‐1. [64] Qin H, Chen M, Yi X, ”ie S, Zhang C, Zhang Y, Lan J, Meng Y, Yuan Y, Jiao C. Identii‐ cation of associated SSR markers for yield component and iber quality traits based on frame map and upland coton collections. PLoS One, 2015; 10: e0118073. DOI: 10.1371/ journal.pone.0118073. [65] Thornsberry JM, Goodman MM, Doebley J, Kresovich S, Nielsen D, ”uckler ES. Dwarf8 polymorphisms associate with variation in lowering time. Nature Genetics, 2001; 28: 286 289. DOI: 10.1038/90135. [66] Paterson, “H. Making genetic maps. In: Genome Mapping in Plants (”iotechnology Intelligence Unit). San Diego, C“: “cademic Press; 1996. p. 23 39. [67] Collard ”CY, Jahufer MZZ, ”rouwer J”, Pang ECK. “n introduction to markers, quantitative trait loci (QTL) mapping and marker‐assisted selection for crop improve‐ ment: the basic concepts. Euphytica, 2005; 142: 169 196. DOI: 10.1007/s10681‐005‐1681‐ 5. [68] Reinisch “J, Dong JM, ”rubaker CL, Stelly DM, Wendel JF, Paterson “H. “ detailed RFLP map of coton, Gossypium hirsutum × Gossypium barbadense: chromosome organi‐ zation and evolution in a disomic polyploid genome. Genetics, 1994; 138: 829 847. PMCID: PMC1206231. [69] Yu J, Zhang K, Li S, Yu S, Zhai M, Wu X, Li S, et al. Mapping quantitative trait loci for lint yield and iber quality across environments in a Gossypium hirsutum × Gossypium barbadense backcross inbred line population. Theoretical and “pplied Genetics, 2013; 126: 275 287. DOI: 10.1007/s00122‐012‐1980‐x. [70] “ltaf J, Stewart McD, Wajahatullah MK, Zhang J. Molecular and morphological genetics of a trispecies F2 population of coton. Proceedings of the ”eltwide Coton Conference, 1997; 1: 448 452, National Coton Council, Memphis, TN. [71] Jiang CX, Wright RJ, El‐Zik KM, Paterson “H. Polyploid formation created unique avenues for response to selection in Gossypium (coton). Proceedings of the National Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 “cademy of Sciences of the United States of “merica, 1998; 95: 4419 4424. DOI: 10.1073/ pnas.95.8.4419. [72] Shappley ZW, Jenkins JN, Meredith WR, McCarty JC. 1998. “n RFLP linkage map of upland coton (Gossypium hirsutum L.). Theoretical and “pplied Genetics, 97: 756 761. DOI: 10.1007/s001220050952. [73] Khan M“, Zhang J, Stewart MCDJ. Integrated molecular map based on a trispeciic F2 population on coton. In: Herber DJ, Richter D“, editors. Proceedings of ”eltwide Coton Improvement Conference; 1998, San Diego, C“. p. 491 492. [74] Khan M“, Stewart JMCD, Zhang J, Myers GO, Cantrell RG. “ddition of new markers to trispeciic coton map. In: Proceedings of ”eltwide Coton Conference; 1999. p. 439. [75] Ulloa M, Meredith WR. Genetic linkage map and QTL analysis of agronomic and iber quality traits in an intraspeciic population. Journal Coton Science, 2000; 4: 161 170. [76] Lacape JM, Nguyen T”, Thibivilliers S, ”ojinov ”, Courtois ”, Cantrell RG, ”urr ”, Hau ”. “ combined RFLP‐SSR‐“FLP map of tetraploid coton based on a Gossypium hirsutum × Gossypium barbadense backcross population. Genome, 2003; 46: 612 626. DOI: 10.1139/ g03‐050. [77] Han Z, Guo W, Song X, Zhang T Genetic mapping of EST derived microsatellites from the diploid Gossypium arboreum in allotetraploid coton. Molecular Genetics and Genomics, 2004; 272: 308 327. DOI: 10.1007/s00438‐004‐1059‐8. [78] Mei M, Syed NH, Gao W, Thaxton PM, Smith CW, Stelly DM, Chen ZJ. Genetic mapping and QTL analysis of iber related traits in coton. Theoretical and “pplied Genetics, 2004; 108: 280 291. DOI: 10.1007/s00122‐003‐1433‐7. [79] Liu S, Saha S, Stelly D, ”urr ”, Cantrell RG. Chromosomal assignment of microsatellite loci in coton. Journal of Heredity, 2000; 91: 326‐332. DOI: 10.1093/jhered/91.4.326. [80] Nguyen T”, Giband M, ”rotier P, Risterucci “M, Lascape JM. Wide coverage of the tetraploid coton genome using newly developed microsatellite markers. Theoretical and “pplied Genetics, 2004; 109: 167 175. DOI: 10.1007/s00122‐004‐1612‐1. [81] Wang FR, Gong YC, Zhang CY, Liu GD, et al. Genetic efects of introgression genomic components from Sea Island coton (Gossypium barbadense L.) on iber related traits in upland coton (G. hirsutum L.). Euphytica, 2011; 181: 41 53. DOI: 10.1007/s10681‐011‐ 0378‐1. [82] Lin Z, He D, Zhang X, Nie Y, Guo X, Feng C, Stewart JMCD. Linkage map construction and mapping QTL to coton ibre quality using SR“P, SSR and R“PD. Plant ”reeding, 2005; 124: 180 187. DOI: 10.1111/j.1439‐0523.2004.01039.x. [83] Park YH, “labady MS, Ulloa M, Sickler ”, Wilkins T“, Yu J, Stelly D, Kohel RJ, El‐Shiny OM, Cantrell RG. Genetic mapping of new coton ibre loci using EST‐derived micro‐ 151 152 Cotton Research satellites in an interspeciic recombinant inbred (RIL) coton population. Molecular Genetics and Genomics, 2005; 274: 428 441. DOI: 10.1007/s00438‐005‐0037‐0. [84] ”abar M, Saranga Y, Iqbal Z, “rif M, Zafar Y, Lubbers E, Chee P. Identiication of QTLs and impact of selection from various environments (dry vs irrigated) on the genetic relationships among the selected coton lines from F6 population using a phylogenetic approach. “frican Journal of ”iotechnology, 2009; 8: 4802 4810. DOI: 10.4314/ ajb.v8i19.65170. [85] Saleem M“, Malik T“., Shakeel “, “shraf M. QTL mapping for some important drought tolerant traits in upland coton. The Journal of “nimal & Plant Science, 2015; 25: 502 509. [86] Shen X, Guo W, Zhu X, Yuan Y, Yu JZ, Kohel RJ, Zhang T. Molecular mapping of QTLs for qualities in three diverse lines in upland coton using SSR markers. Molecular ”reeding, 2005; 15: 169 181. DOI: 10.1007/s11032‐004‐4731‐0. [87] He DH, Lin ZX, Zhang XL, Nie YC, Guo XP, Zhang YX, Li W. QTL mapping for economic traits based on a dense genetic map of coton with PCR‐based markers using the interspeciic cross of Gossypium hirsutum vs Gossypium barbadense. Euphytica, 2007; 153: 181 197. DOI: 10.1007/s10681‐006‐9254‐9. [88] “bdurakhmonov IY, ”uriev ZT, Saha S, Pepper “E, Musaev J“, “lmatov “, Shermatov, SE, Kushanov FN, Mavlonov GT, Reddy, UK, Yu JZ, Jenkins, JN, Kohel RJ, “bdukari‐ mov “. Microsatellite markers associated with lint percentage trait in coton, Gossypium hirsutum. Euphytica, 2007; 156: 141 156. DOI: 10.1007/s10681‐007‐9361‐2. [89] Ynturi P, Jenkins JN, McCarty JC, Gutierrez O“, Saha S. “ssociation of root‐ knot nematode resistance genes with simple sequence repeat markers on two chromosomes in coton. Crop Science, 2006; 46: 2670 2674. DOI: 10.2135/ cropsci2006.05.0319. [90] Song XL, Wang K, Guo WZ, Han ZG, Zhang TZ. Quantitative trait loci mapping of leaf morphological traits and chlorophyll content in cultivated tetraploid coton. “cta ”otanica Sinica, 2005; 47: 13821390. DOI: 10.1139/g04‐126. [91] Rungis D, Llewellyn D, Dennis ES, Lyon ”R. Investigation of the chromosomal location of the bacterial blight resistance gene present in an “ustralian coton (Gossypium hirsutum L.) cultivar. “ustralian Journal of “gricultural Research, 2005; 53: 551 560. DOI: 10.1071/ar04190. [92] Shen XL, Van ”ecelaere G, Kumar P, Davis RF, May OL, Chee P. QTL mapping for resistance to root‐knot nematodes in the M‐120 RNR Upland coton line (Gossypium hirsutum L.) of the “uburn 623 RNR source. Theoretical and “pplied Genetics, 2006; 113: 1539 1549. DOI: 10.1007/s00122‐006‐0401‐4. [93] Wang C, Ulloa M, Roberts P“. Identiication and mapping of microsatellite markers linked to a root‐knot nematode resistance gene (rkn1) in “cala NemX coton (Gossypium Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 hirsutum L.). Theoretical and “pplied Genetics, 2006; 112: 770 777. DOI: 10.1007/ s00122‐005‐0183‐0. [94] Niu C, Hinchlife DJ, Cantrell RG, Wang CL, Roberts P“, Zhang JF. Identiication of molecular markers associated with rootknot nematode resistance in upland coton. Crop Science, 2007; 47: 951 960. DOI: 10.2135/cropsci2006.07.0499. [95] Rahman M, Hussain D, Malik T“, Zafar Y. Genetics of resistance to coton leaf curl disease in Gossypium hirsutum. Plant Pathology, 2005; 54: 764 772. DOI: 10.1111/j.1365‐ 3059.2005.01280.x. [96] Rahman M, “hmed N, “sif M, Zafar Y. Identiication of DN“ markers linked with coton leaf curl disease (CLCD). International Coton Genome Initiative (ICGI) Work‐ shop, 2006; ”rasilia, ”razil. p. 77 78. [97] Lacape JM, Jacobs J, “rioli T, Derijcker R, Forestier N, Chiron D, Llewellyn, Jean J, Thomas E, Viot C. “ new interspeciic, Gossypium hirsutum × G. barbadense, RIL population: towards a uniied consensus linkage map of tetraploid coton. Theoretical and “pplied Genetics, 2009; 119: 281 292. DOI: 10.1007/s00122‐009‐1037‐y. [98] Jubrael J, Udupa S, ”aum M. “ssessment of “FLP‐based genetic relationships among date palm (Phoenix Dactylifera L.) varieties of Iraq. Journal of the “merican Society for Horticultural Science, 2005; 130: 442 447. [99] “ndersen JR, Lubberstedt T. Functional markers in plants. Trends in Plant Science, 2003; 8: 554 560. DOI: 10.1016/j.tplants.2003.09.010. [100] Kalia RK, Rai MK, Kalia S, Singh R, Dhawan “K. Microsatellite markers: an overview of the recent progress in plants. Euphytica, 2011; 177: 309 334. DOI: 10.1007/s10681‐ 010‐0286‐9. [101] Weising K, Nybom H, Wolf K, Kahl G. DN“ ingerprinting in plants: Principles, Methods and “pplications. 2nd ed. ”oca Raton, FL: CRC Press, Taylor & Francis Group; 2005. [102] Gupta P, Varshney R, Sharma P, Ramesh ”. Molecular markers and their applications in wheat breeding. Plant ”reeding, 1999; 118: 369 390. DOI: 10.1046/j.1439‐ 0523.1999.00401.x. [103] Kumar P, Gupta VK, Misra “K, Modi DR, Pandey ”K. Potential of molecular markers in plant biotechnology. Plant Omics Journal, 2009; 2: 141 162. [104] Liu ZJ, Cordes JF. DN“ marker technologies and their applications in aquaculture genetics. “quaculture, 2004; 238: 1 37. DOI:10.1016/j.aquaculture.2004.05.027. [105] ”rubaker CL, Wendel JF. Reevaluating the origin of domesticated coton (Gossypium hirsutum; Malvaceae) using nuclear restriction fragment length polymorphisms (RFLPs). “merican Journal of ”otany, 1994; 81: 1309 1326. DOI: 10.2307/2445407. 153 154 Cotton Research [106] Wright RJ, Thaxton PM, El‐Zik KM, Paterson “H. D‐subgenome bias of Xcm resistance genes in tetraploid Gossypium (coton) suggests that polyploid formation has created novel avenues for evolution. Genetics, 1998; 149: 1987 1996. PMID: 9691052. [107] Karp “, Edwards KJ. DN“ markers: a global overview. In: Caetano “nolles G, Gresshof PM, editors. DN“ Markers: Protocols, “pplications, and Overviews. Wiley‐Liss, Inc. US“; 1997. 364 p. [108] Ulloa M, Meredith JWR, Shappley ZW, Kahler “L. RFLP genetic linkage maps from four F2.3 populations and a joinmap of Gossypium hirsutum L. Theoretical and “pplied Genetics, 2002; 104: 200 208. htp://naldc.nal.usda.gov/download/12760/PDF. [109] Caeteno‐“nnolas. M““P: a versatile and universal tool for genome analysis. Plant Molecular ”iology, 1994; 25: 1011 1026. [110] Ulloa M, Saha S, Jenkins JN, Meredith WRJ, JC Mccarty JR, Stelly DM. Chromosomal assignment of RFLP linkage groups harboring important QTLs on an intraspeciic coton (Gossypium hirsutum L.) joinmap. Journal of Heredity, 2005; 96: 132 144. DOI: 10.1093/jhered/esi020. [111] Khan S“, Hussain D, “skari E, Stewart JMcD, Malik K“. Zafar Y. Molecular phyloge‐ ny of Gossypium species by DN“ ingerprinting. Theoretical and “pplied Genetics, 2000; 101: 931 938. DOI: 10.1007/s001220051564. [112] Rahman M, Hussain D, Zafar Y. Estimation of genetic divergence among elite coton (Gossypium hirsutum L.) cultivars/genotypes by DN“ ingerprinting technology. Crop Science, 2002; 42: 2137 2144. DOI: 10.2135/cropsci2002.2137. [113] Preetha S, Raveendren TS. Molecular marker technology in coton. ”iotechnology and Molecular ”iology Review, 2008; 3: 32 45. [114] ”ardak “. Mapping of genes related to iber and fuzz formation in coton (G. hirsutum L.) genome and QTL analysis. Ph.D. Thesis. Department of Field Crops, March 2012. p. 141. [115] ”adigannavar “, Myers GO, Jones DC. Molecular diversity revealed by “FLP markers in upland coton genotypes. Journal of Crop Improvement, 2012; 26: 627 640. DOI: 10.1080/15427528.2012.664614. [116] Essenberg M, ”ayles M”, Samad R“, Hall J“, ”rinkerhof L“, Verhalen M“. Four near‐ isogenic lines of coton with diferent genes for bacterial blight resistance. Phytopa‐ thology, 2002; 92: 1323 1328. DOI: 10.1094/PHYTO.2002.92.12.1323. [117] Li C, Wang X, Dong N, Zhao H, Xia Z, Wang R, Converse RL. Wang Q. QTL analysis for early‐maturing traits in coton using two upland coton (Gossypium hirsutum L.) crosses. ”reeding Science, 2013; 63: 154 163. DOI: 10.1270/jsbbs.63.154. [118] Xiao J, Wu K, Fang DD, Stelly DM, Yu J, Cantrell RG. New SSR markers for use in coton (Gossypium spp.) improvement. Journal of Coton Science, 2009; 13: 75 157. Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 [119] Qureshi SN, Saha S, Kantety RV, Jenkins JN, Saha S. Molecular biology and physiology: EST‐SSR: a new class of genetic markers in coton. Journal of Coton Science, 2004; 8: 112 123. [120] Reddy MP, Sarla N, Siddiq E“. Inter simple sequence repeat (ISSR) polymorphism and its application in plant breeding. Euphytica, 2002; 128: 9 17. DOI: 10.1023/“: 1020691618797. [121] ”ornet ”, Muller C, Paulus F, ”ranchard ML. Highly informative nature of inter simple sequence repeat (ISSR) sequences ampliied using tri and tetra‐nucleotide primers from DN“ of caulilower (Brassica oleracea var. botrytis L.). Genome, 2002; 45: 890 896. DOI: 10.1139/g02‐061. [122] Russell JR, Fuller JD, Macaulay M, Haz ”G, Jahoor “, et al. Direct comparison of levels of genetic variation among barley accessions detected by RFLPs, “FLPs, SSRs and R“PDs. Theoretical and “pplied Genetics, 1997; 95: 714 722. DOI: 10.1007/ s001220050617. [123] “ltaf MK, Stewart JM, Wajahatullah MK, Zhang JF. Molecular and morphological genetics of a trispecies F2 population of coton. In: Dugger P, Richter D“, editors. Proceedings of the ”eltwide Coton Production Research Conferences. National Coton Council of “merica, Memphis, TN. “nimal Genome VI, January 18 22; 1998. San Diego, California, US“; 1997. p. 448 452. [124] Wu J, Jenkins JN, McCarty JC, Zhong M. “FLP marker associations with agronomic and iber traits in coton. Euphytica, 2007; 153: 153 163. DOI: 10.1007/s10681‐006‐9250‐ 0. [125] Hawkins J, Pleasants, Wendel JF. Identiication of “FLP markers that discriminate between cultivated coton and the Hawaiian island endemic, Gossypium tomentosum Nutall ex Seeman. Genetic Resources and Crop Evolution, 2005; 52: 1069 1078. DOI: 10.1007/s10722‐004‐6115‐z. [126] ”ardakci F. Random ampliied polymorphic DN“ (R“PD) markers. Turkish Journal of ”iology, 2001; : 185 196. [127] Lee SW, Thomas F, Ledig, Johnson DR. Genetic variation at allozyme and R“PD markers in Pinus longaeva (Pinaceae) of the White Mountains, California. “merican Journal of ”otany, 2002; 89: 566 577. PMID: 21665657. [128] Khanam S, Sham “, ”ennezen JL, “ly M“M. “nalysis of molecular marker‐based characterization and genetic variation in date palm (Phoenix dactylifera L.). “JCS, 2012; 6: 1236 1244. [129] Tian J, Deng Z, Zhang K, Yu H, Jiang X, Li C. Genetic “nalyses of Wheat and Molecular Marker‐“ssisted ”reeding, Volume 1, © Science Press, ”eijing and Springer Science+”usiness Media Dordrecht; 2015. DOI: 10.1007/978‐94‐017‐ 7390‐4_2. 155 156 Cotton Research [130] Lan TH, Cook CG, Paterson “H. Identiication of a R“PD marker linked to male fertility restoration gene in coton (Gossypium hirsutum L.). Journal of “gricultural Genomics, 1999; 1: 1 5. [131] Geng CD, Gong ZZ, Huang JQ, Zhang ZC. Identiication of diference between coton cultivars (G. hirsutum) using the R“PD method. Jiangsu Journal of “gricultural Science, 1995; 11: 21 24. [132] Zahra N, Shojaei‐Jesvaghani F, Sheidai M, Farahani F, Omran “, Inter simple sequence repeats (ISSR) and random ampliied polymorphic DN“ (R“PD) analyses of genetic diversity in Mehr coton cultivar and its crossing progenies. “frican Journal of ”io‐ technology, 2011; 10: 11839 11847. DOI: 10.1371/journal.pbio.0030038. [133] Farzaneh T, et al. Cytogenetic and R“PD analysis of coton cultivars and their F1 progenies. Caryologia, 2010; 63: 73 81. DOI: 10.1080/00087114.2010.10589710. [134] Noormohammadi Z, Shojaei‐Jeshvaghani F, Sheidai M, Farahani F, et al. ISSR and R“PD analysis of genetic diversity in Mehr coton cultivar and its crossing progenies. “frican Journal of ”iotechnology, 2011; 10: 11839 11847. DOI: 10.5897/“J”11.1377. [135] Noormohammadi Z, Farahani Y, Sheidai H“M, Ghasemzadeh‐”araki S, “lishah O. Genetic diversity analysis in Opal coton hybrids based on SSR, ISSR, and R“PD markers. Genetics and Molecular Research, 2013; 12: 256 269. DOI: 10.4238/2013.Janu‐ ary.30.12. [136] Ulloa M, “bdurakhmonov IY, Claudia PM, Percy R, Stewart McDJ. Genetic diversity and population structure of coton (Gossypium spp.) of the New World assessed by SSR markers. ”otany, 2013; 91: 251 259. DOI: 10.1139/cjb‐2012‐0192. [137] Wolf K, Schoen ED, Peters‐Van RJ. Optimizing the generation of random ampliied polymorphic DN“ in chrysanthemum. Theoretical and “pplied Genetics, 1993; 86: 1033 1037. DOI: 10.1007/”F00211058. [138] Liu ZJ, Cordes JF. DN“ marker technologies and their applications in aquaculture genetics. “quaculture, 2004. DOI:10.1016/j.aquaculture.2004.05.027 [139] Singh PK, Sharma H, Srivastava N, ”hagyawant SS. “nalysis of genetic diversity among wild and cultivated chickpea genotypes employing ISSR and R“PD markers. “merican Journal of Plant Sciences, 2014; 5: 676 682. DOI: htp://dx.doi.org/10.4236/ajps. 2014.55082. [140] Mishra KK, Fougat RS, ”allani “, Thakur Vinita, Yachana J. Madhumat ”. Potential and application of molecular markers techniques for plant genome analysis. International Journal of Pure & “pplied ”ioscience, 2014; 2: 169 188. [141] ”ornet ”, ”ranchard M. Non‐anchored inter simple sequence repeat (ISSR) markers: reproducible and speciic tools for genome ingerprinting. Plant Molecular ”iology Reporter, 2001; 19: 209 215. DOI: 10.1007/”F02772892. Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 [142] Parkhyia S, Gohel K, Mehta DDR. Genetic diversity analysis of coton (G. hirsutum L.) genotypes using ISSR markers. IJ“PS“, 2014; 1: 7 19. [143] Gupta M, Chyi YS, Romero‐Severson J, Owen JL. “mpliication of DN“ markers from evolutionarily diverse genomes using single primers of simple sequence repeats. Theoretical and “pplied Genetics, 1994; 89: 998 1006. DOI: 10.1007/”F00224530. [144] Tsumura Y, Ohba K, Strauss SH. Diversity and inheritance of inter‐simple sequence repeat polymorphisms in Douglas ir (Pseudotsuga menziesii) and sugi (Cryptomeria japonica). Theoretical and “pplied Genetics, 1996; 92: 40 45. DOI: 10.1007/”F00222949. [145] Liu ”, Wendel JF. Intersimple sequence repeat (ISSR) polymorphisms as a genetic marker system in coton. Molecular Ecology Notes, 2001; 1: 205 208. DOI: 10.1046/j. 1471‐8278.2001.00073.x. [146] Wang G, Mahalingan R, Knap HT. (C‐“) and (G“) anchored simple sequence repeats (“SSRs) generated polymorphism in soybean, Glycine max (L.) Merr. Theoretical and “pplied Genetics, 1998; 96: 1086 1096. DOI: 10.1007/s001220050843. [147] Paran I, Michelmore RW. Development of reliable PCR based markers linked to downy mildew resistance genes in letuce. Theoretical and “pplied Genetics, 1993; 85: 985 993. DOI: 10.1007/”F00215038. [148] Dnyaneshwar W, Preeti C, Joshi K, Patwardhan ”. Development and application of R“PD‐SC“R marker for identiication of Phyllanthus emblica Linn. ”iological and Pharmaceutical ”ulletin, 2006; 2911: 2313 2316. DOI: 10.1248/bpb.29.2313. [149] Li SF, Tang SJ, Cai, WQ. R“PD‐SC“R markers for genetically improved NEW GIFT Nile Tilapia (Oreochrmis niloticus niloticus L.) and their application in strain identiica‐ tion. Zoological Research, 2010; 31: 147 153. DOI: 10.3724/SP.J.1141.2010.02147. [150] Rajesh MK, Jerard ”“, Preethi P, Thomas RJ, Fayas TP, Rachana KE, Karun “. Devel‐ opment of a R“PD‐derived SC“R marker associated with tall‐type palm trait in coconut. Scientia Horticulturae, 2013; 150: 312 316. DOI: 10.1016/j.scienta.2012.11.023. [151] Kumla S, Doolgindachbaporn S, Sudmoon R, Satayasai N. Genetic variation, popula‐ tion structure and identiication of yellow catish, Mystus nemurus (C&V) in Thailand using R“PD, ISSR and SC“R marker. Molecular ”iology Reports, 2012; 9: 5201 5210. DOI: 10.1007/s11033‐011‐1317‐x. [152] Guo W, Zhang T, Shen X, Yu ZJ, Kohel RJ. Development of SC“R marker linked to a major QTL for high iber strength and its usage in molecular‐ marker‐assisted selection in Upland coton. Crop Science, 2003; 43: 2252 2256. DOI: 10.2135/cropsci2003.2252. [153] Jiang C, Wright RJ, Woo SS, DelMonte T“, Paterson “H. QTL analysis of leaf morphol‐ ogy in tetraploid Gossypium (coton). Theoretical and “pplied Genetics, 2000; 100: 409 418. 157 158 Cotton Research [154] Olsen M, Hood L, Cantor C, ”otstein D. “ common language for physical mapping of the human genome. Science, 1989; 245: 1434 1435. DOI: 10.1126/science.2781285. [155] Feng CD, Stewart JMc, Zhang JF. STS markers linked to the Rf 1 fertility restorer gene of coton. Theoretical and “pplied Genetics, 2005; 110: 237 243. DOI: 10.1007/s00122‐ 004‐1817‐3. [156] Rong J, “bbey C, ”owers JE, ”rubaker CL, Chang C, Chee PW, Delmonte T“, Ding X, Garza JJ, Marler ”S, et al. “ 3347‐locus genetic recombination map of sequence tagged sites reveals features of genome organization, transmission and evolution of coton (Gossypium). Genetics, 2004; 166: 389 417. DOI: 10.1534/genetics.166.1.389. [157] Vos P, Hogers R, ”leeker M, Reijans M, Lee van de T, Hornes M, Frijters “, Pot J, Peleman J, Kuiper M, Zabeau M. “FLP: a new technique for DN“ ingerprinting. Nucleic “cids Research, 1995; 23: 4407 4414. PMCID: PMC307397. [158] “kkaya MS, ”hagwat ““, Cregan P”. Length polymorphisms of simple sequence repeat DN“ in soybean. Genetics, 1992; 132: 1131 1139. PMCID: PMC1205234. [159] Roder MS, Korzun V, Wendehake K, Plaschke J, Tixier MH, Leroy P, Ganal MW. “ microsatellite map of wheat. Genetics, 1998; 149: 2007 2023. PMCID: PMC1460256. [160] Gupta PK, Varshney RK. The development and use of microsatellite markers for genetic analysis and plant breeding with emphasis on bread wheat. Euphytica, 2000; 113: 163 185. DOI: 10.1023/“:1003910819967. [161] Jarne P, Lagoda PJL. Microsatellites, from molecules to populations and back. Trends in Ecology & Evolution, 1996; 11: 424 429. DOI: 10.1016/0169‐5347(96)10049‐5. [162] “bdurakhmonov IY, “bdullaev ““, Saha S, ”uriev ZT, “rslanov D, Kuryazov Z, Mavlonov GT, Rizaeva SM, Reddy UK, Jenkins JN, “bdullaev “, “bdukarimov “. Simple sequence repeat marker associated with a natural leaf defoliation trait in tetraploid coton. Journal of Heredity, 2005; 96: 644 653. DOI: 10.1093/jhered/esi097. [163] ”ardak “, ”olek Y. Genetic diversity of diploid and tetraploid cotons determined by SSR and ISSR markers. Turkish Journal of Field Crops, 2012; 17: 139 144. [164] “bdurakhmonov IY, ”uriev ZT, Shermatov SE, Kushanov FN, Makamov “, Shopulatov U, Turaev O, Norov T, “khmedov C, Mirzaakhmedov M, “bdukarimov “. Utilization of natural diversity in Upland coton (G. hirsutum) germplasm collection for pyramid‐ ing genes via marker‐assisted selection program. In: 5th Meeting of the “sian Coton Research and Development Network. February 23 25, 2011. [165] Chee P, Draye X, Jiang CX, Decanini L, Delmonte T“, ”redhauer R, Smith CW, Paterson “H. Molecular dissection of interspeciic variation between Gossypium hirsutum and Gossypium barbadense (coton) by a backcross‐self approach. I. Fiber elongation. Theoretical and “pplied Genetics, 2005; 111: 757 763. DOI: 10.1007/s00122‐005‐2063‐z. Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 [166] Mumtaz H. Identiication of structural and functional genomic markers for iber quality traits in coton using interspeciic population (G. hirsutum × G. barbadense). MPhil Thesis; 2007; Q“ University, Islamabad, Pakistan, [167] Frelichowski JM, Palmer M”, Main D, Tomkins JP, Cantrell RG, Stelly DM, et al. Coton genome mapping with new microsatellites from “cala Maxa ”“C‐ends. Molecular Genetics and Genomics, 2006; 275: 479 491. DOI: 10.1007/s00438006‐0106‐z. [168] “bdalla M, Reddy OUK, Ei‐Zik KM, Pepper “E. Genetic diversity and relationships of diploid and tetraploid coton. Theoretical and “pplied Genetics, 2001; 6: 222 229. DOI: 10.1007/s001220051639. [169] Van EG“, ”owman DT, Calhoun DS, May OL. Changes in the genetic diversity of coton in the US“ from 1970 to 1995. Crop Science, 1998; 38: 33 37. DOI: 10.2135/crops‐ ci1998.0011183X003800010006x. [170] Sapkal DR, Sutar SR, Thakre P”, Patil ”R, Paterson “H, Waghmare VN. Genetic diversity analysis of maintainer and restorer accessions in upland coton (Gossypium hirsutum L.). Journal of Plant ”iochemistry and ”iotechnology, 2011; 20: 20 28. DOI: 10.1007/s13562‐010‐0020‐7. [171] Reddy OUK, Pepper “E, “bdurakhmonov I, Saha S, Jenkins JN, ”rooks T, ”olek Y, El‐ Zik KM. New dinucleotide and trinucleotide microsatellite marker resources for coton genome research. The Journal of Coton Science, 2001; 5: 103 113. [172] Kumpatla SP, Horne EC, Shah MR, Gupta M, Thompson S“. Development of SSR markers: towards genetic mapping in coton (Gossypium hirsutum L.). In: 3rd Interna‐ tional Coton Genome Initiative Workshop, Nanjing, China. Coton Science, 2002; 14: 28. [173] “bdurakhmonov IY, Saha S, Jenkins JN, ”uriev ZT, Shermatov SE, et al. Linkage disequilibrium based association mapping of iber quality traits in G. hirsutum L. variety germplasm. Genetica, 2009; 136: 401 417. DOI: 10.1007/s10709‐008‐9337‐8. [174] Cao Z., Wang P., Zhu X., et al. SSR marker‐assisted improvement of iber qualities in Gossypium hirsutum using Gossypium barbadense introgression. Theoretical and “pplied Genetics, 2014; 14: 587 594. DOI: 10.1007/s00122‐013‐2241‐3. [175] Nie X, Tu J, Wang ”, Zhou X, Lin Z. “ ”IL population derived from G. hirsutum and G. barbadense provides a resource for coton genetics and breeding. PLoS One, 2015; 10: e0141064. DOI: 10.1371/journal.pone.0141064. [176] Wang XQ, Yu Y, Sang J, Wu QZ, Zhang XL, Lin ZX. Intraspeciic linkage map construc‐ tion and QTL mapping of yield and iber quality of Gossypium babrdense. “ustralian Journal of Crop Science, 2013; 7: 1252 1261. [177] Pathak D, ”hatia D. Development of advanced mapping populations in coton. IC“C 2015; XXXIII. 159 160 Cotton Research [178] Huang YF, Poland J“, Wight CP, Jackson EW, Tinker N“. Using genotyping‐by‐ sequencing (G”S) for genomic discovery in cultivated oat. PLoS One, 2014; 9: e102448. DOI: 10.1371/journal.pone.0102448. [179] ”olukbasi MF, Mizrak “, Ozdener G”, Madlener S, Strobel T, Erkan EP, Fan J”, ”reakeield XO, Saydam O. miR‐1289 and Zipcode ‐like sequence enrich mRN“s in microvesicles. Molecular Therapy Nucleic “cids, 2012; 1: e10. DOI: 10.1038/mtna. 2011.2. [180] ”olger ME, Weisshaar ”, Scholz U, Stein N, Usadel ”, Mayer KF. Plant genome sequencing applications for crop improvement. Current Opinion in ”iotechnology, 2014; 26: 31 37. DOI: 10.1016/j.copbio.2013.08.019. [181] Qin YS, Liu RZ, Mei HX, Zhang TZ, Guo WZ. QTL mapping for yield traits in upland coton (Gossypium hirsutum L.). “cta Ecologica Sinica, 2009; 35: 1812 1821. DOI: 10.3724/ SP.J.1006.2009.01812. [182] Li FG, Fan GY, Lu CR, Xiao GH, Zou CS, Kohel RJ, et al. Genome sequence of cultivated Upland coton (Gossypium hirsutum TM‐1). Nature ”iotechnology, 2015; 33: 524 530. DOI: 10.1038/nbt.3208. [183] Chen H, Qian N, Guo WZ, Song QP, Li ”C, Deng FJ, Dong CG, Zhang TZ. Using three overlapped RILs to dissect genetically clustered QTL for iber strength on Chro. D8 in Upland coton. Theoretical and “pplied Genetics, 2009; 119: 605 612. DOI: 10.1007/ s00122‐009‐1070‐x. [184] Zhang K, Zhang J, Ma J, Tang SY, Liu DJ, Teng ZH, et al. Genetic mapping and quan‐ titative trait locus analysis of iber quality traits using a three‐parent composite population in upland coton (Gossypium hirsutum L.). Molecular ”reeding, 2012; 29: 335 348. DOI: 10.1007/s11032‐011‐9549‐y. [185] Liang QZ, Cheng HU, Hua H, Li , Zhao H, Ping JH. Construction of a linkage map and QTL mapping for iber quality traits in upland coton (Gossypium hirsutum L.). Plant Genetics, 2013; 58: 3233‐3243. DOI: 10.1007/s11434‐013‐5807‐1. [186] Islam MS, Zeng LH, Delhom CD, Song HL, Kim HJ, Li P, et al. Identiication of coton iber quality quantitative trait loci using intraspeciic crosses derived from two near‐ isogenic lines difering in iber bundle strength. Molecular ”reeding, 2014; 34: 373 384. DOI: 10.1007/s11032‐014‐0040‐4. [187] Islam MS, Linghe Z, Thyssen GN, Christopher D, Delhom H, Jin K, Ping L, D. Fang. Mapping by sequencing in coton (Gossypium hirsutum) line MD52ne identiied candidate genes for iber strength and its related quality atributes. Theoretical and “pplied Genetics, DOI: 10.1007/s00122‐016‐2684‐4. [188] “bdurakhmonov IY, Shapulatov UM, Shermatov SE, ”uriev ZT, “bdullaev ““, Kushanov FN, Egamberdiev SS, Salahutdinov I”, Ubaydullaeva H“, Makamov “H, Darmanov MM, “yubov MS, Norov TM, Tulanov ““, Mavlonov GT, “bdukarimov Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 “. “chievements and perspectives of coton omics in Uzbekistan. In: Proceedings of the International Coton conference ”remen, 19 21 March 2014, ”remen, Germany. [189] Collin FS, ”rooks LD, Charkravarti ““. DN“ polymorphism discovery resource for research on human genetic variation. Genome Research, 1998; 8: 1229 1231. DOI: 10.1101/gr.8.12.1229. [190] Rafalski J“. “pplications of single nucleotide polymorphisms in crop genetics. Current Opinion in Plant ”iology, 2002; 5: 94‐100. DOI: 10.1016/S1369‐ 5266(02)00240‐6. [191] Zhu YL, Song QJ, Hyten DL, Tassell VCP, Matukumalli LK, Grimm DR, Hyat SM, Fickus EW, Young ND, Cregan P”. Single‐nucleotide polymorphism in soybean. Genetics, 2003; 163: 1123 1134. PMCID: PMC1462490. [192] Krawczak M. Informativity assessment for biallelic single nucleotide polymorphisms. Electrophoresis, 1999; 20: 1676 1681. DOI: 10.1002/(SICI)1522‐ 2683(19990101)20:8<1676::“ID‐ELPS1676>3.0.CO;2‐D. [193] Zhu W, Schlueter SD, ”rendel V. Reined annotation of the “rabidopsis genome by complete expressed sequence tag mapping. Plant Physiology, 2003; 132: 469 484. DOI: 10.1104/pp.102.018101. [194] Wang DG, Fan J”, Siao CJ, ”erno “, Young P, Sapolsky R, Ghandour G, Perkins N, Winchester E, Spencer J, et al. Large‐scale identiication, mapping, and genotyping of single‐nucleotide polymorphisms in the human genome. Science, 1998; 280: 1077 1082. DOI: 10.1126/science.280.5366.1077. [195] He J, Zhao X, Laroche “, Lu ZX, Liu H, Li Z. Genotyping by‐sequencing (G”S), an ultimate marker‐assisted selection (M“S) tool to accelerate plant breeding. Front. Plant Science, 2014; 5: 484. DOI: 10.3389/fpls.2014.004. [196] Thomson MJ, Zhao K, Wright M, McNally KL, Rey J, Tung CW, Reynolds “, Scheler ”, Eizenga G, McClung “, Kim H, Ismail “M, de Ocampo M, Mojica C, Reveche MY, Dilla‐Ermita CJ, Mauleon R, Leung H, ”ustamante C, McCouch SR. High‐throughput single nucleotide polymorphism genotyping for breeding applications in rice using the ”eadXpress platform. Molecular ”reeding, 2012; 29: 875 886. DOI: 10.1007/s11032‐011‐ 9663‐x. [197] Hefner EL. Sorrells, ME, Jannink JL. Genomic selection for crop improvement. Crop Science, 2009; 49: 1 12. DOI: 10.2135/cropsci2008.08.0512. [198] ”ernardo R. Genomewide selection with minimal crossing in self‐pollinated crops. Crop Science, 2010; 50: 624 627. DOI: 10.2135/cropsci2009.05.0250. [199] Jannink JL, Lorenz “J, Iwata H. Genomic selection in plant breeding: from theory to practice. ”rieings in Functional Genomics, 2010; 9: 166 177. DOI: 10.1093/bfgp/elq00. 161 162 Cotton Research [200] Nicolae DL, et al. Trait‐associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GW“S. PLoS Genetics, 2010; 6, e1000888. DOI: 10.1371/ journal.pgen.1000888. [201] Zhang ZS, Hu MC, Zhang J, Liu DJ. Construction of a comprehensive PCR‐based marker linkage map and QTL mapping for iber quality traits in upland coton (Gossypium hirsutum L.). Molecular ”reedIng, 2009; 24: 49 61. DOI: 10.1007/s11032‐009‐ 9271‐1. [202] Mei HX, Zhu XF, Zhang TZ. Favorable QTL alleles for yield and its components identiied by association mapping in Chinese upland coton cultivars. PLoS One, 2013; 8: e82193. DOI: 10.1371/journal.pone.0082193 PMID: 24386089. [203] “n C, Saha S, Jenkins JN, Ma DP, Scheler ”E, et al. Coton (Gossypium spp.) R2R3‐MY” transcription factors SNP identiication, phylogenomic characterization, chromosome localization, and linkage mapping. Theoretical and “pplied Genetics, 2008; 116: 1015 1026. DOI: 10.1007/s00122‐008‐0732‐4. [204] Said JI, Song M, Wang H, Lin Z, Zhang X, Fang DD, Zhang J. “ comparative meta‐ analysis of QTL between intraspeciic Gossypium hirsutum and interspeciic G. hirsutum × G. barbadense population. Molecular Genetics and Genomics, 2015; 290: 1003 1025. DOI 10.1007/s00438‐014‐0963‐9. [205] Deynze V, Stofel K, Lee M, Wilkins T“, Kozik “, Cantrell RG, Yu JZ, Kohel RJ, Stelly DM. Sampling nucleotide diversity in coton. ”MC Plant ”iology, 2009; 9: 125. DOI: 10.1186/1471‐2229‐9‐125. [206] ”yers RL, Harker D”, Yourstone SM, Maughan PJ, Udall J“. Development and mapping of SNP assays in allotetraploid coton. Theoretical and “pplied Genetics, 2012; 124: 1201 1214. DOI: 10.1007/s00122‐0111780‐8. [207] Paciic ”iosciences [Internet]. 2016. “vailable from: htp//www.paciicbiosciences.com. [208] Data D, Gupta S, Chaturvedi SK, Nadarajan N. Molecular Markers in Crop Improve‐ ment. Kanpur: Indian Institute of Pulses Research; 2011. [209] Stoskopf NC, Tomes DT, Christie ”R. Plant ”reeding: Theory and Practice. San Francisco, C“, Oxford: Westview Press Inc.; 1993 [210] Levi “, Paterson “H, ”arak V, Yakir D, Wang ”, Chee W, Saranga Y. Field evaluation of coton near‐isogenic lines introgressed with QTLs for productivity and drought related traits. Molecular ”reeding, 2009; 23: 179 195. DOI: 10.1007/s11032‐008‐9224‐0. [211] Guo WZ, Zhang TZ, Ding YZ, Zhu YC, Shen XL, Zhu XF. Molecular marker‐assisted selection and pyramiding of two QTLs for iber strength in upland coton. “cta Genitica Sinica, 2005; 32: 1275 1285. [212] Jiang GL, Dong Y, Shi J, Ward RW. QTL analysis of resistance to Fusarium head blight in the novel wheat germplasm CJ9306. II. Resistance to deoxylevinaeol accumulation Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 and grain yield loss. Theoretical and “pplied Genetics, 2007; 115: 1043 1052. DOI: 10.1007/s00122‐007‐0630‐1. [213] Ethington SR, Crosbie TM, Edwards MD, Reiter RS, ”ull JK. Molecular markers in commercial breeding program. Crop Science, 2007; 47: S154 S163. DOI: 10.2135/ cropsci2007.04.0015IP”S. [214] Yi C, Guo W, Zhu X, Min L, Zhang T. Pyramiding breeding by marker‐assisted recurrent selection in upland coton II. Selection efects on resistance to Helicoverpa armigera. Scientia “gricultura Sinica, 2004; 37: 801 807. [215] Gutiérrez, Osman “, et al. Identiication of QTL regions and SSR markers associated with resistance to reniform nematode in Gossypium barbadense L. accession G”713. Theoretical and “pplied Genetics, 2011; 122: 271 280. DOI: 10.1007/s00122‐010‐1442‐2. [216] ”aird N“, Eter PD, “twood TS, Currey MC, Shiver “L, Lewis Z“, Selker EU, Cresko W“, Johnson E“. Rapid SNP discovery and genetic mapping using sequenced R“D markers. PLoS One, 2008; 3: e3376. DOI: 10.1371/journal.pone.0003376. [217] Shendure J, Hanli J. Next‐generation DN“ sequencing. Nature ”iotechnology, 2008; 26, 1135 1145. DOI: 10.1038/nbt1486 [218] Deschamps S, Llaca V, Gregory DM, ”us, et al. Genotyping‐by‐sequencing in plants. ”iology, 2012; 1: 460 483. DOI: 10.3390/biology1030460. [219] Quail M“, Smith M, Coupland P, Oto TD, Harris SR, Connor, et al. “ tale of three next generation sequencing platforms: comparison of Ion Torrent, Paciic ”iosciences and Illumina MiSeq sequencers. ”MC Genomics, 2012; 13: 341. DOI: 1471‐2164/13/341. [220] Thudi M, Li Y, Jackson S“, May GD, Varshney RK. Current state‐of‐art of sequencing technologies for plant genomics research. ”rieings in Functional Genomics, 2012; 11: 3 11. DOI: 10.1093/bfgp/elr045. [221] ”entley DR, et al. “ccurate whole human genome sequencing using reversible termi‐ nator chemistry. Nature, 2008; 456: 53 59. DOI: 10.1038/nature07517. [222] Rothberg JM, Hinz W, Rearick TM, Schulz J, Mileski W, Davey M, Leamon JH, Johnson K, Milgrew MJ, Edwards M, Hoon J, Simons JF, Marran D, Myers JW, Davidson JF, ”ranting “, Nobile JR, Puc ”P, Light D, Clark T“, Huber M, ”ranciforte JT, Stoner I”, Cawley SE, Lyons M, Fu Y, Homer N, Sedova M, Miao X, Reed ”, Sabina J, Feierstein E, Schorn M, “lanjary M, Dimalanta E, Dressman D, Kasinskas R, Sokolsky T, Fidanza J“, Namsaraev E, McKernan KJ, Williams “J, Roth GT, ”ustillo J. “n integrated semiconductor device enabling non‐optical genome sequencing. Nature, 2011; 475: 348. DOI: 10.1038/nature10242. [223] Schuster SC. Next‐generation sequencing transforms today s biology. Nature Methods, 2008; 5: 16 18. DOI: 10.1038/nmeth1156. [224] Rounsley S, Marri PR, He Yu, Sisneros R, Goicoechea N, Lee JL, “ngelova SJ, Kudrna “, Luo D, “fourtit M, Desany J, Knight ”, Niazi J, Egholm F, Wing R“. De novo next 163 164 Cotton Research generation sequencing of plant genomes. Rice, 2009; 2: 35 43. DOI: 10.1007/s12284‐009‐ 9025‐z. [225] Morrell PL, ”uckler ES, Ross‐Ibarra J. Crop genomics: advances and applications. Nature Reviews Genetics, 2012; 13: 85 96. DOI: 10.1038/nrg3097. [226] Paterson “H, ”owers JE, ”ruggmann R, Dubchak I, Grimwood J, Gundlach H, Haberer G, Hellsten U, Mitros T, Poliakov “, et al. The Sorghum bicolor genome and the diversiication of grasses. Nature, 547: 2009; 551 556. DOI: 10.1038/nature07723. [227] Huang X, Lu T, Han ”. Re‐sequencing rice genomes: an emerging new era of rice genomics. Trends Genetics, 2013; 29: 225 232. DOI: 10.1016/j.tig.2012.12.001. [228] Li JY, Wang J, Zeigler RS. The 3000 rice genomes project: new opportunities and challenges for future rice research. Giga Science, 2014; 3: 1 3. DOI: 10.1186/2047‐217X‐ 3‐8. [229] Mardis ER. Next‐Generation DN“ sequencing methods. “nnual Review of Genomics and Human Genetics, 2008; 9: 387 402. DOI: 10.1146/annurev.genom.9.081307.164359. [230] Gupta PK, Rustgi S, Mir RR. “rray‐based high‐throughput DN“ markers for crop improvement. Heredity, 2008; 101: 5 18. DOI: 10.1038/hdy.2008.3. [231] Paterson et al. Repeated polyploidization of Gossypium genomes and the evolution of spinnable coton ibres. Nature, 2012; 492: 423 427. DOI: 10.1038/nature11798. [232] Chen X, Li X, Zhang ”, Xu J, Wu Z, Wang ”, et al. Detection and genotyping of restriction fragment associated polymorphisms in polyploid crops with a pseudo‐reference sequence: a case study in allotetraploid Brassica napus. ”MC Genomics, 2013; 14: 346. DOI: 10.1186/1471‐2164‐ 14‐346. [233] Gore M“, Fang DD, Poland J“, Zhang J, Percy RG, Cantrell RG, Lipka “E. Linkage map construction and quantitative trait locus analysis of agronomic and iber quality traits in coton. The Plant Genome, 2014; 7. DOI: 10.3835/plantgenome2013.07.00. [234] “fymetrix [Internet]. 2016. “vailable from: htp://www.afymetrix.com/products services/arrays/speciic/coton.afx. [“ccessed 2016‐03‐25] [235] Malik W, “shraf J, Iqbal ZM, Khan ““, Qayyum “, “bid M“, Noor E, “hmad M“, “bbasi GH. Molecular markers and coton genetic improvement: current status and future prospects. The Scientiic World Journal, 2014; htp://www.hindawi.com/ journals/tswj/2014/607091. [236] Poland J, Endelman J, Dawson J, Rutkoski J, Wu S, Manes Y, Dreisigackere S, Crossae J, Sánchez‐Villedae H, Sorrells M, Jannink JL. Genomic selection in wheat breeding using genotyping‐by‐sequencing. Plant Genome, 2012; 5: 103 113. DOI: 10.3835/ plantgenome2012.06.0006. [237] Poland J“, Rife TW. Genotyping‐by‐sequencing for plant breeding and genetics. Plant Genome, 2012; 5: 92 102. DOI: 10.3835/plantgenome2012.05.0005. Molecular Breeding of Cotton http://dx.doi.org/10.5772/64593 [238] Narum SR, ”uerkle C“, Davey JW, Miller MR, Hohenlohe P“. Genotyping‐by‐ sequencing in ecological and conservation genomics. Molecular Ecology, 2013; 22: 2841 2847. DOI: 10.1111/mec.12350. [239] ”eissinger TM, Hirsch CN, Sekhon RS, Foerster JM, Johnson JM, Mutoni G, Vaillan‐ court ”, ”uell CR, Kaeppler SM, De Leon N. Marker density and read depth for genotyping populations using genotyping‐by‐sequencing. Genetics, 2013; 193: 1073 1081. DOI: 10.1534/genetics.112.147710. [240] Islam MS, Thyssen GN, Jenkins JN, Fang DD. Detection, validation, and application of genotyping‐by‐sequencing based single nucleotide polymorphisms in upland coton. Plant Genome, 2015; DOI: 10.3835/plantgenome2014.3807.0034. [241] Mather DE, Tinker N“, Laberge DE, Edney M, Jones ”L, Rossnagel ”G, Legge WG, ”riggs KG, Irvine R”, Falk DE, Kasha KJ. Regions of the genome that afect grain and malt quality in a North “merican two row barley cross. Crop Science, 1997; 37: 544 554. DOI: 10.2135/cropsci1997.0011183X003700020039x. [242] “bdurakhmonov YI, “bdukarimov “. “pplication of association mapping to under‐ standing the genetic diversity of plant germplasm resources. International Journal of Plant Genomics, 2008. “rticle ID 574927, DOI: 10.1155/2008/574927. [243] Kraakman “TW, Niks RE, Van den ”erg PMMM, Stam P, Van Eeuwijk F“. Linkage disequilibrium mapping of yield and yield stability in modern spring barley cultivars. Genetics, 2004; 168: 435 446. DOI: 10.1534/genetics.104.026831. [244] Mammadov W, Chen R, Ren, et al. Development of highly polymorphic SNP markers from the complexity reduced portion of maize (Zea mays L.) genome for use in marker‐ assisted breeding. Theoretical and “pplied Genetics, 2010; 121: 577 588. DOI: 10.1007/ s00122‐010‐1331‐8. [245] Truong HT, Ramos “M, Yalcin F, De Ruiter M, Van der Poel HJ, Huvenaars KH, Hogers RCJ, Van Encke‐vort LJG, Janssen “, Van Orsouw NJ, Van Eijk MJ. Sequence‐ based genotyping for marker discovery and co‐dominant scoring in germplasm and popu‐ lations. PLoS One 2012; 7: e37565. DOI: 10.1371/journal.pone.0037565. [246] Van Poecke RM, Maccaferri M, Tang J, Truong HT, Janssen “, Van Orsouw NJ, et al. Sequence‐based SNP genotyping in durum wheat. Plant ”iotechnology Journal 2013; 11: 809 817. DOI: 10.1111/pbi.12072. [247] “bdurakhmonov IY, “bdukarimov “. “pplication of association mapping to under‐ standing the genetic diversity of plant germplasm resources. International Journal of Plant Genomics, 2008. “rticle ID: 574927, DOI: 10.1155/2008/574927. [248] ”oopathi MN, Thiyagu K, Urbi ”, Santhoshkumar M, Gopikrishnan “, “ravind S, Swapnashri G, Ravikesavan R. Marker‐assisted breeding as next‐generation strategy for genetic improvement of productivity and quality: can it be realized in coton? International Journal of Plant Genomics, 2011; 2011: 670104. DOI: 10.1155/2011/670104. 165 166 Cotton Research [249] Comparative Evolutionary Genomics of Coton [Internet]. 2016. “vailable from: htp:// cotonevolution.info. [“ccessed 2016‐03‐25]. [250] National Center for ”iotechnology Information [Internet]. 2016. “vailable from: htp:// www.ncbi.nlm.nih.gov. [“ccessed 2016‐03‐25]. [251] TropGENE Database [Internet]. 2016. “vailable from: htp://tropgenedb.cirad.fr. [“ccessed 2016‐03‐25]. [252] The Plant Genome Mapping Laboratory [Internet]. 2016. “vailable from: htp:// www.plantgenome.uga.edu/. [“ccessed 2016‐03‐25]. [253] ”“CMan resources at Plant Genome Mapping Laboratory [Internet]. 2016. “vailable from: htp://www.plantgenome.uga.edu. [“ccessed 2016‐03‐25]. [254] Till ”J, Comai L, Henikof S, TILLING and ECOTILLING for crop improvement. Genomics‐assisted crop improvement. Genomics “pproaches and Platforms, 20071: 333 349. [255] Simsek O, Kacar Y“. Discovery of mutations with TILLING and ECOTILLING in plant genomes. Scientiic Research and Essays, 2010; 5: 3799 3802. htp://www.academi‐ cjournals.org/SRE. [256] Mehboob R, Shaheen T, Iqbal M, “shraf, et al. Coton genetic resources. “ review. “gronomy for Sustainable Development, Springer Verlag/EDP Sciences/INR“, 2012; 32: 419 432. DOI: 10.1007/s13593‐011‐0051‐z. [257] “uld D, Light GG, Fokar M, ”echere E, “llen RD. Mutagenesis system for genetic analysis of Gossypium. In: Paterson “H, editor. Genetics and genomics of coton. vol. 3. Springer Inteurnational Publishing, NY, US“.; 2009. p. 209 226. DOI: 10.1007/978‐0‐ 387‐70810‐2_9. [258] Ng PC, Henikof S. SIFT: predicting amino acid changes that afect protein function. Nucleic “cids Research, 2003; 31: 3812 3814. DOI: 10.1093/nar/gkg509. [259] Taylor NE, Greene E“. P“RSESNP: a tool for the analysis of nucleotide polymorphisms. Nucleic “cids Research, 2003; 31: 3808 3811. DOI: 10.1093/nar/gkg574. [260] Project “ligned Related Sequences and Evaluate SNPs [Internet]. 2016. “vailable from: htp://www.proweb.org/parsesnp. [“ccessed 2016‐03‐25].