Preliminary transcriptomic analysis of peripheral blood from German Shepherd dogs with degenerative joint disease for the identification of diagnostic biomarkers.

OBJECTIVE: Degenerative joint disease (DJD) includes a group of disorders characterised by the deterioration of the articular cartilage. In this study, we investigated the transcriptomic profile of peripheral blood in German Shepherd dogs with DJD to identify putative diagnostic biomarkers. METHODS: Differential gene expression (DGE) and gene ontology (GO) analyses of the bulk RNA-seq experiment were performed in a cohort of 12 adult dogs (five cases and seven controls, classified by clinical and radiographic analyses). RESULTS: Radiographs of cases revealed severe signs of progressive DJD. Two up-regulated (LOC106559672 and THBS4) and one down-regulated (LOC106559235) differentially expressed genes (adjusted p value < 0.05) were identified. The DGE with log2 fold change < -1.5 and > 1.5 and non-adjusted p < 0.01 were selected for GO analysis. No significant enrichment terms were observed in the selected threshold. CONCLUSION: The gene-encoding protein THBS4 is correlated with DJD severity and long noncoding RNA LOC106559235 is probably involved in the DJD process. The THBS4 gene should be considered a good biomarker for DJD in dogs. Future studies using independent cohorts will be necessary to validate the present results.

Prediction of Non-Genotoxic Carcinogenicity Based on Genetic Profiles of Short Term Exposure Assays.

Non-genotoxic carcinogens are substances that induce tumorigenesis by non-mutagenic mechanisms and long term rodent bioassays are required to identify them. Recent studies have shown that transcription profiling can be applied to develop early identifiers for long term phenotypes. In this study, we used rat liver expression profiles from the NTP (National Toxicology Program, Research Triangle Park, USA) DrugMatrix Database to construct a gene classifier that can distinguish between non-genotoxic carcinogens and other chemicals. The model was based on short term exposure assays (3 days) and the training was limited to oxidative stressors, peroxisome proliferators and hormone modulators. Validation of the predictor was performed on independent toxicogenomic data (TG-GATEs, Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System, Osaka, Japan). To build our model we performed Random Forests together with a recursive elimination algorithm (VarSelRF). Gene set enrichment analysis was employed for functional interpretation. A total of 770 microarrays comprising 96 different compounds were analyzed and a predictor of 54 genes was built. Prediction accuracy was 0.85 in the training set, 0.87 in the test set and increased with increasing concentration in the validation set: 0.6 at low dose, 0.7 at medium doses and 0.81 at high doses. Pathway analysis revealed gene prominence of cellular respiration, energy production and lipoprotein metabolism. The biggest target of toxicogenomics is accurately predict the toxicity of unknown drugs. In this analysis, we presented a classifier that can predict non-genotoxic carcinogenicity by using short term exposure assays. In this approach, dose level is critical when evaluating chemicals at early time points.

Linking soil, water, and honey composition to assess the geographical origin of argentinean honey by multielemental and isotopic analyses.

The objective of this research was to investigate the development of a reliable fingerprint from elemental and isotopic signatures of Argentinean honey to assess its geographical provenance. Honey, soil, and water from three regions (Córdoba, Buenos Aires, and Entre Ríos) were collected. The multielemental composition was determined by ICP-MS. δ(13)C was measured by isotopic ratio mass spectrometry, whereas the (87)Sr/(86)Sr ratio was determined using thermal ionization mass spectrometry. The data were analyzed by chemometrics looking for the association between the elements, stable isotopes, and honey samples from the three studied areas. Honey samples were differentiated by classification trees and discriminant analysis using a combination of eight key variables (Rb, K/Rb, B, U, (87)Sr/(86)Sr, Na, La, and Zn) presenting differences among the studied regions. The application of canonical correlation analysis and generalized procrustes analysis showed 91.5% consensus between soil, water, and honey samples, in addition to clear differences between studied areas. To the authors' knowledge, this is the first report demonstrating the correspondence between soil, water, and honey samples using different statistical methods, showing that elemental and isotopic honey compositions are related to soil and water characteristics of the site of origin.

Elemental and isotopic fingerprint of Argentinean wheat. Matching soil, water, and crop composition to differentiate provenance.

The aim of this study was to investigate if elemental and isotopic signatures of Argentinean wheat can be used to develop a reliable fingerprint to assess its geographical provenance. For this pilot study we used wheat cultivated at three different regions (Buenos Aires, Córdoba, and Entre Ríos), together with matching soil and water. Elemental composition was determined by ICP-MS. δ(13)C and δ(15)N were measured by isotopic ratio mass spectrometry, while (87)Sr/(86)Sr ratio was determined using thermal ionization mass spectrometry. Wheat samples from three sampling sites were differentiated by the combination of 11 key variables (K/Rb, Ca/Sr, Ba, (87)Sr/(86)Sr, Co, Mo, Zn, Mn, Eu, δ(13)C, and Na), demonstrating differences among the three studied regions. The application of generalized Procrustes analysis showed 99.2% consensus between cultivation soil, irrigation water, and wheat samples, in addition to clear differences between studied areas. Furthermore, canonical correlation analysis showed significant correlation between the elemental and isotopic profiles of wheat and those corresponding to both soil and water (r(2) = 0.97, p < 0.001 and r(2) = 0.96, p < 0.001, respectively). To our knowledge, this is the first report demonstrating the correspondence between soil, water, and wheat samples using different statistical methods, showing that wheat elemental and isotopic compositions are mainly related to soil and irrigation water characteristics of the site of growth.

A case of multiple assignments (paternity/maternity) in an equine-out breeding system.

Recently, the use of DNA markers has provided a more accurate method of identifying individuals and verifying parentage. In this report, we describe foal assignment in a farm bred jumping horses (Silla argentino). Ten mares were freely served by two stallions, resulting in nine foals. Weaning occurred without registration of the mare of each offspring, resulting in a failure to identify either the mare or the sire of each foal. Animals were typed using 12 microsatellite systems and four biochemical polymorphisms in order to determine the paternity/maternity of each foal. We used the CERVUS program to evaluate the parentage of each offspring. It was possible to determine maternity in eight cases, and paternity in all of them. We concluded that this set of codominant markers analyzed following a likelihood-based approach included in the CERVUS package, are useful tools to solve parentage assignments in domestic horses.

Assignment of paternity in a judicial dispute between two neighbor Holstein dairy farmers.

DNA profiling was used as evidence to assign paternity in a dispute between two neighbors in a judicial case of undue appropriation of cattle offspring from five alleged Holstein sires. Five offspring were genotyped using ten genetic markers (nine microsatellites and the BOLA-DRB3 locus). The computer program CERVUS was used to estimate the LOD score values and the confidence of paternity assignments. The results presented here show that three out of five paternity cases were assigned at 95% of confidence to a single sire with a LOD score ranging from 2.53 to 3.55. A fourth male was assigned using its delta value. Finally, all alleged sires were excluded from the paternity of the fifth offspring, probably due to the existence of an non-sampled male in the studied population. We concluded that the likelihood-based approach, included into CERVUS program, was a powerful tool in cattle kinship analysis when dealing with judicial dispute particularly when the dam's genotype was absent, allowing the assignments of paternity at 95% level of confidence in situations usually used by dairy and beef cattle producers in Argentine (e.g., multi-sire pasture mating).