Cotton is the world's leading cash crop, but it lags behind other major crops for marker-assisted breeding due to limited polymorphisms and a genetic bottleneck through historic domestication. This underlies a need for characterization, tagging, and utilization of existing natural polymorphisms in cotton germplasm collections. Here we report genetic diversity, population characteristics, the extent of linkage disequilibrium (LD), and association mapping of fiber quality traits using 202 microsatellite marker primer pairs in 335 G. hirsutum germplasm grown in two diverse environments, Uzbekistan and Mexico. At the significance threshold (r (2) >or= 0.1), a genome-wide average of LD extended up to genetic distance of 25 cM in assayed cotton variety accessions. Genome wide LD at r (2) >or= 0.2 was reduced to approximately 5-6 cM, providing evidence of the potential for association mapping of agronomically important traits in cotton. Results suggest linkage, selection, inbreeding, population stratification, and genetic drift as the potential LD-generating factors in cotton. In two environments, an average of ~20 SSR markers was associated with each main fiber quality traits using a unified mixed liner model (MLM) incorporating population structure and kinship. These MLM-derived significant associations were confirmed in general linear model and structured association test, accounting for population structure and permutation-based multiple testing. Several common markers, showing the significant associations in both Uzbekistan and Mexican environments, were determined. Between 7 and 43% of the MLM-derived significant associations were supported by a minimum Bayes factor at 'moderate to strong' and 'strong to very strong' evidence levels, suggesting their usefulness for marker-assisted breeding programs and overall effectiveness of association mapping using cotton germplasm resources.

The emergence of genome manipulation methods promises a real revolution in biotechnology and genetic engineering. Targeted editing of the genomes of living organisms not only permits investigations into the understanding of the fundamental basis of biological systems but also allows addressing a wide range of goals towards improving productivity and quality of crops. This includes the creation of plants with valuable compositional properties and with traits that confer resistance to various biotic and abiotic stresses. During the past few years, several novel genome editing systems have been developed; these include zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and clustered regularly interspaced short palindromic repeats/Cas9 (CRISPR/Cas9). These exciting new methods, briefly reviewed herein, have proved themselves as effective and reliable tools for the genetic improvement of plants.

RNA interference (RNAi), is a powerful new technology in the discovery of genetic sequence functions, and has become a valuable tool for functional genomics of cotton (Gossypium sp.). The rapid adoption of RNAi has replaced previous antisense technology. RNAi has aided in the discovery of function and biological roles of many key cotton genes involved in fiber development, fertility and somatic embryogenesis, resistance to important biotic and abiotic stresses, and oil and seed quality improvements as well as the key agronomic traits including yield and maturity. Here, we have comparatively reviewed seminal research efforts in previously used antisense approaches and currently applied breakthrough RNAi studies in cotton, analyzing developed RNAi methodologies, achievements, limitations, and future needs in functional characterizations of cotton genes. We also highlighted needed efforts in the development of RNAi-based cotton cultivars, and their safety and risk assessment, small and large-scale field trials, and commercialization.

Background: The involvement of small RNAs in cotton fiber development is under explored. The objective of this work was to directly clone, annotate, and analyze small RNAs of developing ovules to reveal the candidate small interfering RNA/microRNAs involved in cotton ovule and fiber development.

Molecular markers associated withWber development traits have the potential to play a key role in understanding of cotton Wber development. Seventeen SSRs out of 304 markers tested from MGHES (EST-SSR), JESPR (genomic SSR), and TMB (BAC-derived SSR) collections showed signiWcant linkage associations (using a Kurskal-Wallis non-parametric test) with lint percentage QTL in a set of recombinant inbred cotton lines (RILs) segregating for lint percentage. The permutation test of these potential markers associated with lint percentage QTL(s) determined that 12 SSR markers have stable estimates, exceeding empirically chosen threshold signiWcance values at or above = 0.01. Interval mapping demonstrated that 9 SSRs with stable critical LOD threshold values at = 0.01 have signiWcant QTL eVect. Multiple QTL-mapping (MQM) revealed that at least, two highly signiWcant Wber development QTLs exist around regions TMB0471 and MGHES-31 (explained about 23-59% of the phenotypic variation of lint percentage) and around markers MGHES-31 and TMB0366 (accounted for 5.4-12.5% phenotypic variation of lint percentage). These markers, in particular Wber-speciWc EST-SSRs, might be the possible 'candidate' loci contributing for Wber development in cotton. BAC-derived SSRs associated with Wber trait are the possible markers that are useful for the identiWcation of physical genomic contigs that contain Wber development genes. Several lint percentage trait associated SSR markers have been located to chromosomes 12, 18, 23, and 26 using deletion analysis in aneuploid chromosome substitution lines. Outcomes of the work may prove useful in understanding I. Y. Abdurakhmonov and S. Saha contributed equally to the work