**1. Introduction**

Cotton is a crop of immense importance as being a dominant source of fiber and oil from cottonseed all over the world [1]. The improvement of cotton fiber quality has become more important because of changes in spinning technology and ever-increasing demands of fiber. Cotton is grown in more than 80 countries, and contributes to the world economy as a raw material for textile industry [2].

*Gossypium*" genus is made up of about 52 species of which 47 are diploid and 7 are as allotetraploids [3–7]. Of all the species of the genus, two most common

diploids are *G. arboreum* L., *G. herbaceum* L., while *G. hirsutum* L., and *G. barbadense* L. are considered as the most commercially valuable tetraploids. *G. hirsutum*, is characterized by high yield, moderate fiber quality and wide adaptability contributes for 95% of overall cotton production [8]; while *G. barbadense* (Pima, and Egyptian) increases superior fiber quality [9, 10].

Efforts for broadening the genetic base of *Gossypium* genus have not generated successful outcomes due to the complex and large genetic architecture of its genome. Moreover, owing to its developmental barriers, genetic studies have not yet been able to produce the required traits in cotton [11]. Association among markers and characters can be used for fastening the breeding program. The hereditary variation present among the gene pool land races can be exploited by applying the mapping based on linkage disequilibrium. It will speed up the cotton breeding through identification of markers among trait of interest and ensure molecular breeding. Single reproducibility of genetic marker which govern a specific appearance on sequence of nucleotides can be analyzed with genome wide association [12, 13]. Association mapping relies upon the magnitude of different pair of genes for population analysis. Moreover, this mapping shows powerful connection between required character and a genetic marker while nonrandom combination between two quantitative trait loci or markers manifests linkage disequilibrium [8]. The valuable information about the origin of an individual is determined with the degree and the size of the population [13, 14]. Many loci relating to polygenic characters have been determined via genetic maps and linkage disequilibrium (LD) was measured in humans through diverse analysis methods [15, 16]. Population based polygenic characters mapping for desired traits became a widely used technique thanks to the innovations in omics and availability of advanced bioinformatic tools for analyzing genetic variations [17]. The ultimate benefits of this technique includes the ability to work with a large number of loci, producibilty of highly saturated maps, its speed and its low cost [18].
