Antibodies for the Coat Protein of Cotton Leafroll Dwarf Virus Detect Commelina sp. as an Intermediary Host for Cotton Blue Disease.

The cotton blue disease, caused by the cotton leafroll dwarf virus (CLRDV), leads to dwarfism, leaf rolling, and production loss in susceptible cotton varieties. To develop an enzyme-linked immunosorbent assay (ELISA) test to detect the virus in cotton and weeds, peptides based on the coat protein were used to produce polyclonal (α-GQE, α-PRN, and α-INK) and monoclonal (α-GQE, α-PRN, and α-NKF) antibodies. All six were tested as capture antibodies, and polyclonal α-GQE and the monocle onal α-NKF were labeled with the enzyme alkaline phosphatase and used as detection antibodies for a double antibody sandwich (DAS) ELISA method, in which p-nitrophenyl phosphate was added and measured by absorbance at 405 nm. The DAS-ELISA sandwich was efficient in discriminating between healthy and diseased plant extracts. The ELISA methodology detected the virus in the weeds Commelina sp., which was confirmed by RT-PCR. The monoclonal antibodies may be used to develop other diagnostic procedures.

Genetic diversity and structure of natural populations of Gossypium mustelinum, a wild relative of cotton, in the basin of the De Contas River in Bahia, Brazil.

Gossypium mustelinum is a wild cotton relative found only in the semiarid region of Bahia state in Brazil, and changes caused by humans in the natural habitat of this species have endangered the existence of several natural populations. Information about the occurrence and genetic composition of these populations is necessary to design effective conservation measures. The aim of this study was to characterize the in situ maintenance mode and assess the genetic diversity of G. mustelinum populations in the basin of the De Contas River. A sample of 205 G. mustelinum specimens was collected from the margins of the Jacaré, Riacho Quixaba, Riacho Serra Azul, and Riacho Riachão rivers and genotyped using 13 SSR primer pairs. In general, all G. mustelinum populations exhibit inadequate in situ maintenance, predominantly due to the deforestation of riparian vegetation and herbivory. The observed total genetic diversity of G. mustelinum was significant (H E = 0.489), highly structured (F ST = 0.534), and organized in homozygous genotypes (F IS = 0.873). The high observed inbreeding level is consistent with the predominance of self-fertilization and geitonogamy (t m = 0.234). In addition, the pattern of genetic structure tended to form groups that coincided with the collection sites, i.e., first clustering within subpopulations, then within populations, and finally within the closest populations. Thus, the observed genetic diversity is likely to be rapidly lost, and conservation measures should therefore be undertaken.

Complete sequence of a new bipartite begomovirus infecting cotton plants in Brazil.

Begomoviruses are plant viruses responsible for severe losses in important crops, such as beans, cassavas, tomatoes, and cotton, around the world. Here, we report the first full-genome sequence of a bipartite begomovirus species collected from cotton plants in Brazil.

Meta-analysis of cotton fiber quality QTLs across diverse environments in a Gossypium hirsutum x G. barbadense RIL population.

BACKGROUND: Cotton fibers (produced by Gossypium species) are the premier natural fibers for textile production. The two tetraploid species, G. barbadense (Gb) and G. hirsutum (Gh), differ significantly in their fiber properties, the former having much longer, finer and stronger fibers that are highly prized. A better understanding of the genetics and underlying biological causes of these differences will aid further improvement of cotton quality through breeding and biotechnology. We evaluated an inter-specific Gh x Gb recombinant inbred line (RIL) population for fiber characteristics in 11 independent experiments under field and glasshouse conditions. Sites were located on 4 continents and 5 countries and some locations were analyzed over multiple years. RESULTS: The RIL population displayed a large variability for all major fiber traits. QTL analyses were performed on a per-site basis by composite interval mapping. Among the 651 putative QTLs (LOD > 2), 167 had a LOD exceeding permutation based thresholds. Coincidence in QTL location across data sets was assessed for the fiber trait categories strength, elongation, length, length uniformity, fineness/maturity, and color. A meta-analysis of more than a thousand putative QTLs was conducted with MetaQTL software to integrate QTL data from the RIL and 3 backcross populations (from the same parents) and to compare them with the literature. Although the global level of congruence across experiments and populations was generally moderate, the QTL clustering was possible for 30 trait x chromosome combinations (5 traits in 19 different chromosomes) where an effective co-localization of unidirectional (similar sign of additivity) QTLs from at least 5 different data sets was observed. Most consistent meta-clusters were identified for fiber color on chromosomes c6, c8 and c25, fineness on c15, and fiber length on c3. CONCLUSIONS: Meta-analysis provided a reliable means of integrating phenotypic and genetic mapping data across multiple populations and environments for complex fiber traits. The consistent chromosomal regions contributing to fiber quality traits constitute good candidates for the further dissection of the genetic and genomic factors underlying important fiber characteristics, and for marker-assisted selection.

Predicting performance of soybean populations using genetic distances estimated with RAPD markers

In order to verify whether genetic distance (GD) is associated with population mean (PM), genetic variance (GV) and the proportion of superior progenies generated by each cross in advanced generations of selfing (PS), the genetic distances between eight soybean lines (five adapted and three non-adapted) were estimated using 213 polymorphic RAPD markers. The genetic distances were partitioned according to Griffing's Model I Method 4 for diallel analysis, i.e., GDij = GD+ GGDi+ GGDj + SGDij. Phenotypic data were recorded for seed yield and plant height for 25 out of 28 populations of a diallel set derived from the eight soybean lines and evaluated from F2:8 to F2:11 generations. No significant correlation for seed yield was detected between GD and GV, while negative correlations were detected between GD and PM and between GD and PS (r = -0.74** and -0.75**, respectively). Similar results were observed for the correlation between GGDi + GGDj and PM and between GGDi + GGDj and PS (r = -0.78** and -0.80**, respectively). No significant correlation was detected for plant height. The magnitudes of the correlations for seed yield were high enough to allow predictions of the potential of the populations based on RAPD markers