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.

A full-sibling F1 population comprising 153 individuals from the cross of 'Regent' x 'Lemberger' was employed to construct a genetic map based on 429 molecular markers. The newly-bred red grapevine variety 'Regent' has multiple field-resistance to fungal diseases inherited as polygenic traits, while 'Lemberger' is a traditional fungus-susceptible cultivar. The progeny segregate quantitatively for resistances to Plasmopara viticola and Uncinula necator, fungal pathogens that threaten viticulture in temperate areas. A double pseudo-testcross strategy was employed to construct the two parental maps under high statistical stringency for linkage to obtain a robust marker frame for subsequent quantitative trait locus (QTL) analysis. In total, 185 amplified fragment length polymorphism, 137 random amplified polymorphic DNA, 85 single sequence repeat and 22 sequence characterized amplified region or cleaved amplified polymorphic sequence markers were mapped. The maps were aligned by co-dominant or doubly heterozygous dominant anchor markers. Twelve pairs of homologous linkage groups could be integrated into consensus linkage groups. Resistance phenotypes and segregating characteristics were scored as quantitative traits in three or four growing seasons. Interval mapping reproducibly localized genetic factors that correlated with fungal disease resistances to specific regions on three linkage groups of the maternal 'Regent' map. A QTL for resistance to Uncinula necator was identified on linkage group 16, and QTLs for endurance to Plasmopara viticola on linkage groups 9 and 10 of 'Regent'. Additional QTLs for the onset of berry ripening ("veraison"), berry size and axillary shoot growth were identified. Berry color segregated as a simple trait in this cross of two red varieties and was mapped as a morphological marker. Six markers derived from functional genes could be localized. This dissection of polygenic fungus disease resistance in grapevine allows the development of marker-assisted selection for breeding, the characterization of genetic resources and the isolation of the corresponding genes.

No abstract

No abstract

Limited polymorphism and narrow genetic base, due to genetic bottleneck through historic domestication, highlight a need for comprehensive characterization and utilization of existing genetic diversity in cotton germplasm collections. In this study, 288 worldwide Gossypium barbadense L. cotton germplasm accessions were evaluated in two diverse environments (Uzbekistan and USA). These accessions were assessed for genetic diversity, population structure, linkage disequilibrium (LD), and LD-based association mapping (AM) of fiber quality traits using 108 genome-wide simple sequence repeat (SSR) markers. Analyses revealed structured population characteristics and a high level of intra-variability (67.2%) and moderate interpopulation differentiation (32.8%). Eight percent and 4.3% of markers revealed LD in the genome of the G. barbadense at critical values of r2 ≥ 0.1 and r2 ≥ 0.2, respectively. The LD decay was on average 24.8 cM at the threshold of r2 ≥ 0.05. LD retained on average distance of 3.36 cM at the threshold of r2 ≥ 0.1. Based on the phenotypic evaluations in the two diverse environments, 100 marker loci revealed a strong association with major fiber quality traits using mixed linear model (MLM) based association mapping approach. Fourteen marker loci were found to be consistent with previously identified quantitative trait loci (QTLs), and 86 were found to be new unreported marker loci. Our results provide insights into the breeding history and genetic relationship of G. barbadense germplasm and should be helpful for the improvement of cotton cultivars using molecular breeding and omics-based technologies.

No abstract

As it is known, a significant part of the yield of agricultural crops is lost due to harmful organisms, including diseases. The article reveals the data on the widespread types of plant diseases (rot, wilting, deformation, the formation of tumors, pustules, etc.) and their symptoms. Early identification of the pathogen type of plant infection is of high significance for disease control. Various methods are used to diagnose pathogens of disease on plant. This article discusses the review of the literature data on traditional methods for diagnosis of plant pathogens, such as visual observation, microscopy, mycological analysis, and biological diagnostics or the use of indicator plants. Rapid and reliable detection of plant disease and identification of its pathogen is the first and most important stage in disease control. Early identification of the cause of the disease allows timely selection of the proper protection method and ensures prevention of crop losses. There are a number of traditional methods for identifying plant diseases, however, in order to ensure the promptness and reliability of diagnostics, as well as to eliminate the shortcomings inherent in traditional diagnostics, in recent years, new means and technologies for identifying pathogens have been developed and introduced into practice. As well as the article provides information on such innovative methods of diagnosis of diseases and identification of their pathogens, which are used widely in the world today, such as immunodiagnostics, molecular-genetic (and phylogenetic) identification, mass spectrometry, etc.

A collection of isolates of Fusarium oxysporum f. sp. vasinfectum (FOV) from cotton in Uzbekistan was characterized based on candidate gene sequencing approach. As a first step, cotton seedlings were artificially re-infected with randomly selected 8 unknown FOV isolates from the collection, FOV strains were re-isolated, and monospore cultures were obtained for genomic DNA preparation. Candidate genes such as elongation factor (EF-1α), beta-tubulin (BT), and ribosomal DNA (rDNA) were sequenced from the genomic DNAs of these unknown Uzbekistan FOV isolates and a set of 13 known races of FOV (races 1, 2, 3, 4, 6, 7, 8, and Australian VCG1112), collected from world research centers. A parsimony based phylogenetic analysis of known races of FOV together with unknown FOV isolates from the Uzbekistan collection clearly suggested that Uzbekistan FOV genotypes can be classified as race 1, 2 &6, race 3, and race 4 or 7. Based on EF-1α pair-wise genetic distances, no difference was observed between races 4 and 7 of FOV. Results from our research provided for the first time a comprehensive study on the identification of FOV races collected from different regions of Uzbekistan. In addition, this study will help breeders to develop resistance management strategies to combat the Fusarium wilt disease by breeding resistant cotton lines in Uzbekistan.