Typical and atypical manifestations of Anaplasma phagocytophilum infection in dogs

Eighteen clinically ill dogs, naturally infected with Anaplasma phagocytophilum, were examined at a veterinary practice in Baxter, Minnesota. A clinical examination, complete blood cell count, enzyme- linked immunosorbent assay (ELISA) for A phagocytophilum, Borrelia burgdorferi, and Ehrlichia canis antibodies and Dirofilaria immitis antigen, and a polymerase chain reaction test for A phagocytophilum DNA were obtained for all dogs. Physical examination findings included fever, arthropathy, lymphadenopathy, epistaxis, acute gastritis, cervical hyperpathia, and central nervous system dysfunction. Complete blood cell count abnormalities included thrombocytopenia, morulae in neutrophils, anemia, leukopenia, eosinopenia, lymphopenia, and monocytosis. Seroreactivity to A phagocytophilum was found in 61%, B burgdorferi antibodies in 17%, and D immitis antigen in 5% of the dogs. Fever, arthropathy, neurologic dysfunction, and epistaxis are clinical syndromes that can be associated with A phagocytophilum infection. Treatment with doxycycline resulted in rapid resolution of clinical signs in all dogs.     

Molecular identification of Echinococcus granulosus genotypes (G1 and G7) isolated from pigs in Mexico

With the aim of genotyping Echinococcus granulosus cysts found in Mexican livestock, we collected hydatid cysts from the livers and lungs of pigs in slaughterhouses in the state of Morelos, Central Region of Mexico. DNA was extracted from the parasites and examined by polymerase chain reaction (PCR) of rDNA internal transcribed spacer 1 (ITS1-PCR), Eg9-PCR, Eg16-PCR, and PCR-restriction fragment length polymorphism (PCR-RFLP). In addition, fragments of the genes coding for mitochondrial cytochrome c oxidase subunit 1 (CO1) and NADH dehydrogenase 1 (ND1) were sequenced. Two different genotypes of E. granulosus were unequivocally identified, the common sheep genotype, G1, and the common pig genotype, G7. The G1 genotype of E. granulosus has not been previously demonstrated in Mexico. Because of its recognized infectivity in humans, G1 genotype is a direct threat to human health and its presence in Mexico is consequently of immediate public health importance and epidemiological relevance.     

Pasteurella multocida contains multiple immunogenic haemin- and haemoglobin-binding proteins

Iron-dependent outer membrane proteins (IROMPs) play an important role in bacterial pathogenesis and present several attributes of potential vaccine candidates. TBLASTN analysis of the Pasteurella multocida Pm70 genome using the same molecules of other bacterial pathogens as a query identified eight putative haemin and haemoglobin receptors for this organism. Quantitative binding assays have demonstrated that the proteins PM0040, PM0236, PM0741, PM1081, PM1428, PM0592 and HgbA bind both haemin and haemoglobin, whereas PM0576 and PM1282 ORFs only bind either haemoglobin or haemin, respectively. Furthermore, Western blot analysis showed that P. multocida-infected mice generate specific antibodies against PM0040, PM0236, PM0741, PM1081, PM1428, PM0592 and HgbA proteins. Nevertheless, inoculation of mice with any single one of these receptors alone did not protect against P. multocida infection.     

Large-scale deployment of a rice 6 K SNP array for genetics and breeding applications

Background

Fixed arrays of single nucleotide polymorphism (SNP) markers have advantages over reduced representation sequencing in their ease of data analysis, consistently higher call rates, and rapid turnaround times. A 6 K SNP array represents a cost-benefit “sweet spot” for routine genetics and breeding applications in rice. Selection of informative SNPs across species and subpopulations during chip design is essential to obtain useful polymorphism rates for target germplasm groups. This paper summarizes results from large-scale deployment of an Illumina 6 K SNP array for rice.

Results

Design of the Illumina Infinium 6 K SNP chip for rice, referred to as the Cornell_6K_Array_Infinium_Rice (C6AIR), includes 4429 SNPs from re-sequencing data and 1571 SNP markers from previous BeadXpress 384-SNP sets, selected based on polymorphism rate and allele frequency within and between target germplasm groups. Of the 6000 attempted bead types, 5274 passed Illumina’s production quality control. The C6AIR was widely deployed at the International Rice Research Institute (IRRI) for genetic diversity analysis, QTL mapping, and tracking introgressions and was intensively used at Cornell University for QTL analysis and developing libraries of interspecific chromosome segment substitution lines (CSSLs) between O. sativa and diverse accessions of O. rufipogon or O. meridionalis. Collectively, the array was used to genotype over 40,000 rice samples. A set of 4606 SNP markers was used to provide high quality data for O. sativa germplasm, while a slightly expanded set of 4940 SNPs was used for O. sativa X O. rufipogon populations. Biparental polymorphism rates were generally between 1900 and 2500 well-distributed SNP markers for indica x japonica or interspecific populations and between 1300 and 1500 markers for crosses within indica, while polymorphism rates were lower for pairwise crosses within U.S. tropical japonica germplasm. Recently, a second-generation array containing ~7000 SNP markers, referred to as the C7AIR, was designed by removing poor-performing SNPs from the C6AIR and adding markers selected to increase the utility of the array for elite tropical japonica material.

Conclusions

The C6AIR has been successfully used to generate rapid and high-quality genotype data for diverse genetics and breeding applications in rice, and provides the basis for an optimized design in the C7AIR.

     

Factorial analysis of the effect of sugarbeet vinasses on agroecological indices in horticultural field

The impact on soil of applying sugarbeet vinasses （V） was analyzed through a field experiment in horticulture greenhouse, arranged in a 23 factorial design. Two levels of three independent variables--application of V, use of polyethylene cover （PC） on the soil. and soil depth （D）---on various dependent variables were studied. Vinasses favoured crop yield and reduced the number of Meloidogyne incognita juveniles in soil. The concentrations ofN. P and K increased with the interaction VxD, with PC also increasing N concentration. The amounts of humic acids and humin decreased with D; fulvic acid concentration increased with V, but decreased with the interaction VxPC. Soil physical factors were improved mainly with D and V. Aromaticity of humic acid-like fractions increased ~＇itb V. In general, V showed significant effects mainly on the topsoil, suggesting low leaching risks. The results indicate that the levels of the independent factors improving a group of variables were not the same that those contributing to another group. Therefore, their best combination should be determined for each scenario to achieve optimum agroecological performance.     

Genetic diversity and population structure of a common bean (Phaseolus vulgaris L.) collection from Calabria (Italy)

Eighty-seven Phaseolus vulgaris landraces, still cultivated in Calabria (Italy), were investigated in order to study the patterns of common bean genetic diversity in this region, to better understand the evolutionary development of beans in Europe and to properly manage these genetic resources. Four American accessions and five Italian varieties were also included. Different markers, such as 12 microsatellites, seed traits, phaseolins and 100-seed weight were combined with different statistical approaches. For each microsatellite, expected (H _e ) and observed (H _o ) heterozygosities, polymorphism information content (PIC), probability of identity (PI) and homozygosity were calculated. Furthermore, in Calabrian group of bean landraces, total (N _a ) and private (N _pa ) number of alleles, observed (H _o ), expected heterozygosities (H _e ) and allelic richness (AR) were calculated. Genetic distances among landraces were estimated using Nei’s coefficient and a cluster analysis using the UPGMA algorithm was performed. The results clearly indicated that: (1) Calabrian germplasm showed a high level of diversity (H _e  = 0.595); (2) Mesoamerican and Andean gene pools were clearly distinguished in Calabrian germplasm, with the Andean gene pool predominating (83 %); (3) Calabrian landraces were largely hybridized within and between the gene pools. A model-based approach, using the STRUCTURE software, was adopted. Six groups, including 4 of Andean origin and one of Mesoamerican origin were identified. Even more interesting, a small group (8 %) showed a distinct genetic structure, in which interspecific hybridizations with runner bean (Phaseolus coccineus L.) could have occurred. Nevertheless, a relatively high proportion of Calabrian bean landraces (12.6 %) was derived from intra and interspecific hybridizations.     

Discrimination of ‘San Marzano’ accessions: A comparison of minisatellite, CAPS and SSR markers in relation to morphological traits

‘San Marzano’ (SM) is one of the most widely known tomato (Solanum lycopersicum L.) cultivars, and is a classic example of a local variety with a premium value. Unfortunately, the original cultivated form is underrepresented in the Protected Denomination of Origin (PDO) area because of the incidence of contaminant and phenotypically similar genotypes. Our aim was to examine the ability of three DNA marker systems (minisatellite, cleaved amplified polymorphic sequence (CAPS) and simple sequence repeat (SSR)) to reveal the genetic diversity of tomato accessions that were, based on a morphological analysis, very similar. The data indicate that both minisatellites and SSRs can be used to genetically distinguish the analysed materials. Furthermore, these two marker systems depict relationships consistent with the hierarchal pattern obtained by the morphological data. As locally cultivated tomato accessions are often characterised by some degree of genetic variability, our results will be valuable in facilitating the purification, management and breeding of tomato germplasms. The differences between the marker systems employed are also discussed in relation to their usefulness in the agro-food chain.     

Spatial evaluation of soil salinity using the WET sensor in the irrigated area of the Segura river lowland

The electrical conductivity of the water within the soil pores (EC_p) measured with the WET sensor, appears to be a reliable estimate of soil salinity. A methodology combining the use of the WET sensor along with geostatistics was developed to delimit and evaluate soil salinity within an irrigated area under arid to semiarid Mediterranean climate in SE Spain. A systematic random sampling of 104 points was carried out. The association between EC_p and the saturation‐extract electrical conductivity (EC_se) was assessed by means of correlation analysis. The semivariograms for EC_p were obtained at three different soil depths. Interpolation techniques, such as ordinary kriging and cokriging, were applied to obtain EC_p levels in the unknown places. For each one of the soil depths, a model able to predict EC_se from EC_p was developed by means of ordinary least squares regression analysis. A good correlation (r = 0.818, p < 0.001) between EC_p and EC_se was found. Spherical spatial distribution was the best model to fit to experimental semivariograms of EC_p at 10, 30, and 50 cm soil depths. Nevertheless, cokriging using the EC_p of an adjacent soil depth as an auxiliary variable provided the best results, compared to ordinary kriging. An analytical propagation‐error methodology was found to be useful to ascertain the contribution of the spatial interpolation and ordinary least squares analysis to the uncertainty of the EC_se mapping. This methodology allowed us to identify 98% of the study area as affected by salinity problems within a rooting depth of 50 cm, with the threshold of EC_se value at 2 dS m^–1. However, considering the crops actually grown and 10% potential reduction yield, the soil‐salinity‐affected area decreased to 83%. The use of sensors to measure soil salinity in combination with geostatistics is a cost‐effective way to draw maps of soil salinity at regional scale. This methodology is applicable to other agricultural irrigated areas under risk of salinization.