High-throughput genotyping arrays provide a standardized resource for plant breeding communities that are useful for a breadth of applications including high-density genetic mapping, genome-wide association studies (GWAS), genomic selection (GS), complex trait dissection, and studying patterns of genomic diversity among cultivars and wild accessions. We have developed the CottonSNP63K, an Illumina Infinium array containing assays for 45,104 putative intraspecific single nucleotide polymorphism (SNP) markers for use within the cultivated cotton species Gossypium hirsutum L. and 17,954 putative interspecific SNP markers for use with crosses of other cotton species with G. hirsutum. The SNPs on the array were developed from 13 different discovery sets that represent a diverse range of G. hirsutum germplasm and five other species: G. barbadense L., G. tomentosum Nuttal × Seemann, G. mustelinum Miers × Watt, G. armourianum Kearny, and G. longicalyx J.B. Hutchinson and Lee. The array was validated with 1,156 samples to generate cluster positions to facilitate automated analysis of 38,822 polymorphic markers. Two high-density genetic maps containing a total of 22,829 SNPs were generated for two F2 mapping populations, one intraspecific and one interspecific, and 3,533 SNP markers were co-occurring in both maps. The produced intraspecific genetic map is the first saturated map that associates into 26 linkage groups corresponding to the number of cotton chromosomes for a cross between two G. hirsutum lines. The linkage maps were shown to have high levels of collinearity to the JGI G. raimondii Ulbrich reference genome sequence. The CottonSNP63K array, cluster file and associated marker sequences constitute a major new resource for the global cotton research community.

ited on sandy or on loamy sediments. Therefore, it is important to study not only the extent of surface spatial Analysis and interpretation of spatial variability of soils is a keyvariability, but also the distribution of subsurface and stone in site-specific farming. Soil survey maps may have up to 0.41ha inclusions of dissimilar soils within a mapping unit. The objectives deep soil horizons. of this study were to determine the degree of spatial variability of soil Among the various soil physical properties, K s and physical properties and variance structure, and to model the sampling related measures are reported to have the highest statisinterval of alluvial floodplain soils. Soil profiles (n ϭ 209) from 18 tical variability (Biggar and Nielsen, 1976). Bouma parallel transects were sampled with a mean separation distance of (1973) stressed the need for more studies on field vari-79.4 m. Each profile was classified into surface, subsurface, and deep ability of K s and soil water retention curves. Stockton horizons. Structural analysis of soil bulk density (b), sand, clay, satuand Warrick (1971) indicated that variability in K s is rated hydraulic conductivity (K s), volumetric water content (v) at both a function of soil depth and position in the landseven pressure potentials (⌿ a) (Ϫ1, Ϫ10, Ϫ33, Ϫ67, Ϫ100, Ϫ500, and scape, as well as experimental errors in measuring K s. Ϫ1500 kPa) were modeled for the three horizons. Variance of soil Cameron (1978) sampled clay loam soils at six depths physical properties varied from as low as 0.01% (b) to as high as 1542% (K s). The LSD test indicated significant (P Ͻ 0.05) differences from five grid-sampled locations in a 225-m 2 plot. He in sand, clay, b , K s , and v at various ⌿ a. Geostatistical analyses used the desorption method to determine soil water illustrated that the spatially dependent stochastic component was preretention curves at pressure heads ranging from Ϫ10 to dominant over the nugget effect. Structured semivariogram functions Ϫ500 kPa to calculate K s. He found no consistent trend of each variable were used in generating fine-scale kriged contour across sampling depths in pressure head values from maps. Overall autocorrelation, Moran's I, indicated a 400-m sampling Ϫ10 to Ϫ500 kPa, but the shape and magnitude of the range would be adequate for detection of spatial structure of sand, average water retention curve differed among locations. silt, clay, and a 100-m sampling range for soil hydraulic properties He further reported that the coefficient of variation of and b. The magnitude and spatial patterns soil physical property soil water content ranged from 4.3 to 13% in the surface variability have implications for variable rate applications and design layer and from 2.4 to 6.5% in the deeper layers. In a of soil sampling strategies in alluvial floodplain soils. study of spatial variability in soil hydraulic properties, Vieira et al. (1981) used variogram, kriging, and cokriging techniques to determine the magnitude of spatial J. Iqbal, Dep. of Agricultu...

The narrow genetic base of cultivated cotton germplasm is hindering the cotton productivity worldwide. Although potential genetic diversity exists in Gossypium genus, it is largely 'underutilized' due to photoperiodism and the lack of innovative tools to overcome such challenges. The application of linkage disequilibrium (LD)-based association mapping is an alternative powerful molecular tool to dissect and exploit the natural genetic diversity conserved within cotton germplasm collections, greatly accelerating still 'lagging' cotton marker-assisted selection (MAS) programs. However, the extent of genome-wide linkage disequilibrium (LD) has not been determined in cotton. We report the extent of genome-wide LD and association mapping of fiber quality traits by using a 95 core set of microsatellite markers in a total of 285 exotic Gossypium hirsutum accessions, comprising of 208 landrace stocks and 77 photoperiodic variety accessions. We demonstrated the existence of useful genetic diversity within exotic cotton germplasm. In this germplasm set, 11-12% of SSR loci pairs revealed a significant LD. At the significance threshold (r(2)>/=0.1), a genome-wide average of LD declines within the genetic distance at <10 cM in the landrace stocks germplasm and >30 cM in variety germplasm. Genome wide LD at r(2)>/=0.2 was reduced on average to approximately 1-2 cM in the landrace stock germplasm and 6-8 cM in variety germplasm, providing evidence of the potential for association mapping of agronomically important traits in cotton. We observed significant population structure and relatedness in assayed germplasm. Consequently, the application of the mixed liner model (MLM), considering both kinship (K) and population structure (Q) detected between 6% and 13% of SSR markers associated with the main fiber quality traits in cotton. Our results highlight for the first time the feasibility and potential of association mapping, with consideration of the population structure and stratification existing in cotton germplasm resources. The number of SSR markers associated with fiber quality traits in diverse cotton germplasm, which broadly covered many historical meiotic events, should be useful to effectively exploit potentially new genetic variation by using MAS programs.

Genetic linkage maps play fundamental roles in understanding genome structure, explaining genome formation events during evolution, and discovering the genetic bases of important traits. A high-density cotton (Gossypium spp.) genetic map was developed using representative sets of simple sequence repeat (SSR) and the first public set of single nucleotide polymorphism (SNP) markers to genotype 186 recombinant inbred lines (RILs) derived from an interspecific cross between Gossypium hirsutum L. (TM-1) and G. barbadense L. (3-79). The genetic map comprised 2072 loci (1825 SSRs and 247 SNPs) and covered 3380 centiMorgan (cM) of the cotton genome (AD) with an average marker interval of 1.63 cM. The allotetraploid cotton genome produced equivalent recombination frequencies in its two subgenomes (At and Dt). Of the 2072 loci, 1138 (54.9%) were mapped to 13 At-subgenome chromosomes, covering 1726.8 cM (51.1%), and 934 (45.1%) mapped to 13 Dt-subgenome chromosomes, covering 1653.1 cM (48.9%). The genetically smallest homeologous chromosome pair was Chr. 04 (A04) and 22 (D04), and the largest was Chr. 05 (A05) and 19 (D05). Duplicate loci between and within homeologous chromosomes were identified that facilitate investigations of chromosome translocations. The map augments evidence of reciprocal rearrangement between ancestral forms of Chr. 02 and 03 versus segmental homeologs 14 and 17 as centromeric regions show homeologous between Chr. 02 (A02) and 17 (D02), as well as between Chr. 03 (A03) and 14 (D03). This research represents an important foundation for studies on polyploid cottons, including germplasm characterization, gene discovery, and genome sequence assembly.

Chromosome identities were assigned to 15 linkage groups of the RFLP joinmap developed from four intraspecific cotton (Gossypium hirsutum L.) populations with different genetic backgrounds (Acala, Delta, and Texas Plains). The linkage groups were assigned to chromosomes by deficiency analysis of probes in the previously published joinmap, based on genomic DNA from hypoaneuploid chromosome substitution lines. These findings were integrated with QTL identification for multiple fiber and yield traits. Overall results revealed the presence of 63 QTLs on five different chromosomes of the A subgenome (chromosomes-03, -07, -09, -10, and -12) and 29 QTLs on the three different D subgenome (chromosomes-14 Lo, -20, and the long arm of -26). Linkage group-1 (chromosome-03) harbored 26 QTLs, covering 117 cM with 54 RFLP loci. Linkage group-2, (the long arm of chromosome-26) harbored 19 QTLs, covering 77.6 cM with 27 RFLP loci. Approximately 49% of the putative 92 QTLs for agronomic and fiber quality traits were placed on the above two major joinmap linkage groups, which correspond to just two different chromosomes, indicating that cotton chromosomes may have islands of high and low meiotic recombination like some other eukaryotic organisms. In addition, it reveals highly recombined and putative gene abundant regions in the cotton genome. QTLs for fiber quality traits in certain regions are located between two RFLP markers with an average of less than one cM (approximately 0.4-0.6 Mb) and possibly represent targets for map-based cloning. Identification of chromosomal location of RFLP markers common to different intra- and interspecific-populations will facilitate development of portable framework markers, as well as genetic and physical mapping of the cotton genome.

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The fruiting sites at which cotton, Gossypium hirsutum L., plants set bolls that are harvested influence how well the plants tolerate insects. The objective of this research was to determine the fruiting patterns of eight cultivars of cotton in terms of fruiting sites of harvestable bolls when planted in a conventional pattern of rows spaced 1‐m apart with a plant population of approximately 95 000 plants ha−1 for 2 yr in Mississippi. Descriptive terms are defined as follows: (i) sympodium—a fruiting branch; (ii) monopodium—a vegetative branch; (iii) node—the place on the main stem where sympodia monopodiarise, we numbered the nodes beginning with the cotyledeonary node as number one; (iv) position—refers to the order which buds (potential bolls) are produced on a sympodinm branch; and (v) fruiting site—any specific node‐position combination. Cultivars compared and their release dates were: Stoneville 213, 1962; Stoneville 506, 1980; Stoneville 825, 1979; Tamcot CAMD‐E, 1979; Deltapine 50, 1984; McNair 235, 1975; DES 119, 1986; and Deltapine 20, 1985. Bolls at position one on sympodial branches produced 66 to 75% of total yield; those at position two produced 18 to 21%; all other positions on sympodial branches produced from 2 to 4% of total yield. Monopodial branches produced from 3 to 9% of the total yield. Sympodial branches from Nodes 9 through 14 produced the bulk of the lint in all cultivars. Distribution of lint over sympodia among cultivars was significantly different for positions one and two, with the newer, early maturing cultivars producing significantly more lint from sympodial branches at Nodes 6 through 8 than the older cultivar Stoneville 213. Tamcot CAMD‐E, McNair 235, and Deltapine 20 also produced less lint on monopodial branches than Stoneville 213. This research provides valuable information needed to more effectively manage the production of the newer, early maturing cuitivars of cotton presently being grown in the mid‐South.

BackgroundUpland cotton (Gossypium hirsutum L.) accounts for about 95% of world cotton production. Improving Upland cotton cultivars has been the focus of world-wide cotton breeding programs. Negative correlation between yield and fiber quality is an obstacle for cotton improvement. Random-mating provides a potential methodology to break this correlation. The suite of fiber quality traits that affect the yarn quality includes the length, strength, maturity, fineness, elongation, uniformity and color. Identification of stable fiber quantitative trait loci (QTL) in Upland cotton is essential in order to improve cotton cultivars with superior quality using marker-assisted selection (MAS) strategy.ResultsUsing 11 diverse Upland cotton cultivars as parents, a random-mated recombinant inbred (RI) population consisting of 550 RI lines was developed after 6 cycles of random-mating and 6 generations of self-pollination. The 550 RILs were planted in triplicates for two years in Mississippi State, MS, USA to obtain fiber quality data. After screening 15538 simple sequence repeat (SSR) markers, 2132 were polymorphic among the 11 parents. One thousand five hundred eighty-two markers covering 83% of cotton genome were used to genotype 275 RILs (Set 1). The marker-trait associations were analyzed using the software program TASSEL. At p < 0.01, 131 fiber QTLs and 37 QTL clusters were identified. These QTLs were responsible for the combined phenotypic variance ranging from 62.3% for short fiber content to 82.8% for elongation. The other 275 RILs (Set 2) were analyzed using a subset of 270 SSR markers, and the QTLs were confirmed. Two major QTL clusters were observed on chromosomes 7 and 16. Comparison of these 131 QTLs with the previously published QTLs indicated that 77 were identified before, and 54 appeared novel.ConclusionsThe 11 parents used in this study represent a diverse genetic pool of the US cultivated cotton, and 10 of them were elite commercial cultivars. The fiber QTLs, especially QTL clusters reported herein can be readily implemented in a cotton breeding program to improve fiber quality via MAS strategy. The consensus QTL regions warrant further investigation to better understand the genetics and molecular mechanisms underlying fiber development.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-397) contains supplementary material, which is available to authorized users.