Improved estimation of inbreeding and kinship in pigs using optimized SNP panels

BACKGROUND: Traditional breeding programs consider an average pairwise kinship between sibs. Based on pedigree information, the relationship matrix is used for genetic evaluations disregarding variation due to Mendelian sampling. Therefore, inbreeding and kinship coefficients are either over or underestimated resulting in reduction of accuracy of genetic evaluations and genetic progress. Single nucleotide polymorphism (SNPs) can be used to estimate pairwise kinship and individual inbreeding more accurately. The aim of this study was to optimize the selection of markers and determine the required number of SNPs for estimation of kinship and inbreeding. RESULTS: A total of 1,565 animals from three commercial pig populations were analyzed for 28,740 SNPs from the PorcineSNP60 Beadchip. Mean genomic inbreeding was higher than pedigree-based estimates in lines 2 and 3, but lower in line 1. As expected, a larger variation of genomic kinship estimates was observed for half and full sibs than for pedigree-based kinship reflecting Mendelian sampling. Genomic kinship between father-offspring pairs was lower (0.23) than the estimate based on pedigree (0.26). Bootstrap analyses using six reduced SNP panels (n = 500, 1000, 1500, 2000, 2500 and 3000) showed that 2,000 SNPs were able to reproduce the results very close to those obtained using the full set of unlinked markers (n = 7,984-10,235) with high correlations (inbreeding r > 0.82 and kinship r > 0.96) and low variation between different sets with the same number of SNPs. CONCLUSIONS: Variation of kinship between sibs due to Mendelian sampling is better captured using genomic information than the pedigree-based method. Therefore, the reduced sets of SNPs could generate more accurate kinship coefficients between sibs than the pedigree-based method. Variation of genomic kinship of father-offspring pairs is recommended as a parameter to determine accuracy of the method rather than correlation with pedigree-based estimates. Inbreeding and kinship coefficients can be estimated with high accuracy using ≥2,000 unlinked SNPs within all three commercial pig lines evaluated. However, a larger number of SNPs might be necessary in other populations or across lines

Differential response of human basophil activation markers: a multi-parameter flow cytometry approach

<p>Abstract</p> <p>Background</p> <p>Basophils are circulating cells involved in hypersensitivity reactions and allergy but many aspects of their activation, including the sensitivity to external triggering factors and the molecular aspects of cell responses, are still to be focused. In this context, polychromatic flow cytometry (PFC) is a proper tool to investigate basophil function, as it allows to distinguish the expression of several membrane markers upon activation in multiple experimental conditions. </p> <p>Methods</p> <p>Cell suspensions were prepared from leukocyte buffy coat of K2-EDTA anticoagulated blood specimens; about 1500-2500 cellular events for each tested sample, gated in the lymphocyte CD45dim area and then electronically purified as HLADRnon expressing/CD123bright, were identified as basophilic cells. Basophil activation with fMLP, anti-IgE and calcium ionophore A23187 was evaluated by studying up-regulation of the indicated membrane markers with a two-laser six-color PFC protocol.</p> <p>Results</p> <p>Following stimulation, CD63, CD13, CD45 and the ectoenzyme CD203c up-regulated their membrane expression, while CD69 did not; CD63 expression occurred immediately (within 60 sec) but only in a minority of basophils, even at optimal agonist doses (in 33% and 14% of basophils, following fMLP and anti-IgE stimulation respectively). CD203c up-regulation occurred in the whole basophil population, even in CD63non expressing cells. Dose-dependence curves revealed CD203c as a more sensitive marker than CD63, in response to fMLP but not in response to anti-IgE and to calcium ionophore.</p> <p>Conclusion</p> <p>Use of polychromatic flow cytometry allowed efficient basophil electronic purification and identification of different behaviors of the major activation markers. The simultaneous use of two markers of activation and careful choice of activator are essential steps for reliable assessment of human basophil functions.</p

Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change

Changes in scores on health status questionnaires are difficult to interpret. Several methods to determine minimally important changes (MICs) have been proposed which can broadly be divided in distribution-based and anchor-based methods. Comparisons of these methods have led to insight into essential differences between these approaches. Some authors have tried to come to a uniform measure for the MIC, such as 0.5 standard deviation and the value of one standard error of measurement (SEM). Others have emphasized the diversity of MIC values, depending on the type of anchor, the definition of minimal importance on the anchor, and characteristics of the disease under study. A closer look makes clear that some distribution-based methods have been merely focused on minimally detectable changes. For assessing minimally important changes, anchor-based methods are preferred, as they include a definition of what is minimally important. Acknowledging the distinction between minimally detectable and minimally important changes is useful, not only to avoid confusion among MIC methods, but also to gain information on two important benchmarks on the scale of a health status measurement instrument. Appreciating the distinction, it becomes possible to judge whether the minimally detectable change of a measurement instrument is sufficiently small to detect minimally important changes

Genetics of Microenvironmental Sensitivity of Body Weight in Rainbow Trout (Oncorhynchus mykiss) Selected for Improved Growth

Microenvironmental sensitivity of a genotype refers to the ability to buffer against non-specific environmental factors, and it can be quantified by the amount of residual variation in a trait expressed by the genotype’s offspring within a (macro)environment. Due to the high degree of polymorphism in behavioral, growth and life-history traits, both farmed and wild salmonids are highly susceptible to microenvironmental variation, yet the heritable basis of this characteristic remains unknown. We estimated the genetic (co)variance of body weight and its residual variation in 2-year-old rainbow trout (Oncorhynchus mykiss) using a multigenerational data of 45,900 individuals from the Finnish national breeding programme. We also tested whether or not microenvironmental sensitivity has been changed as a correlated genetic response when genetic improvement for growth has been practiced over five generations. The animal model analysis revealed the presence of genetic heterogeneity both in body weight and its residual variation. Heritability of residual variation was remarkably lower (0.02) than that for body weight (0.35). However, genetic coefficient of variation was notable in both body weight (14%) and its residual variation (37%), suggesting a substantial potential for selection responses in both traits. Furthermore, a significant negative genetic correlation (−0.16) was found between body weight and its residual variation, i.e., rapidly growing genotypes are also more tolerant to perturbations in microenvironment. The genetic trends showed that fish growth was successfully increased by selective breeding (an average of 6% per generation), whereas no genetic change occurred in residual variation during the same period. The results imply that genetic improvement for body weight does not cause a concomitant increase in microenvironmental sensitivity. For commercial production, however, there may be high potential to simultaneously improve weight gain and increase its uniformity if both criteria are included in a selection index

ARIA-EAACI statement on asthma and COVID-19 (June 2, 2020)

peer reviewed[No abstract available

Basophil stimulation and signaling pathways

Despite growing use of flow cytometry to analyze the functional characteristics of primary basophils the intracellular signaling cascades that control their ability to elaborate various inflammatory mediators and cytokines remain comparatively obscure. Additionally, some studies require the analysis of pro-allergic and inflammatory mediators, such as histamine, LTC4, and various basophil-derived cytokines (e.g., IL-4 and IL-13). Elucidation of intracellular signaling proteins by Western blotting, cytosolic free calcium concentration by spectrofluorophotometry, and detection of mediator releases, as well as analysis of gene expressions by RT-PCR, generally require relatively large numbers of purified basophils. In selected assays, flow cytometry can enable the analysis of relatively low cell numbers and purity for the expression of intracellular signaling proteins or measurement of cytosolic free calcium concentrations by basophil-specific gating strategies. Unfortunately, many aspects of signal transduction relevant to human basophils cannot be readily extrapolated from the use of basophil or mast cell lines. This chapter therefore focuses on how to employ primary human basophils for studying mediator releases and signaling characteristics

Trend in dairy sheep BLG genotype found with repeatability test-day model.

A total of 19.207 test-days, collected on 4 farms from 1999-2006 and belonging to 1109 Valle del Belice dairy sheep were analyzed with a repeatability model. After strict outlier analysis 17.747 records were retained. Animals were reared in an extensive system resulting in large environmental influences. However, significant genetic variation was detected in production traits (milk production mean=1336 stdg=93 g/d, fat+protein 167 stdg=12 g/d). Heritability was only 3% while the interaction year by month of test-day explained 27% of the variation. A protein and DNA analysis program was initiated in order to facilitate selection to maintain these flocks under these conditions. In total 427 animals were typed for the -lactoglobulin locus. Using the recorded pedigree this genotype information was spread over the entire population. The trend in frequency for the AA genotype was significantly negative (p-value=.0057), as were trends in milk yield and lactation length. Possibly farmers have a preference for the BB animals. Relations with production traits were indicative for this trend, but not significant. A possible explanation is the relevant, but non significant difference in length of the lactation between AA and BB animals

The diagnostic value of specific IgE to Ara h 2 to predict peanut allergy in children is comparable to a validated and updated diagnostic prediction model

Background: A diagnostic prediction model for peanut allergy in children was recently published, using 6 predictors: sex, age, history, skin prick test, peanut specific immunoglobulin E (sIgE), and total IgE minus peanut sIgE. Objectives: To validate this model and update it by adding allergic rhinitis, atopic dermatitis, and sIgE to peanut components Ara h 1, 2, 3, and 8 as candidate predictors. To develop a new model based only on sIgE to peanut components. Methods: Validation was performed by testing discrimination (diagnostic value) with an area under the receiver operating characteristic curve and calibration (agreement between predicted and observed frequencies of peanut allergy) with the Hosmer-Lemeshow test and a calibration plot. The performance of the (updated) models was similarly analyzed. Results: Validation of the model in 100 patients showed good discrimination (88%) but poor calibration (P < .001). In the updating process, age, history, and additional candidate predictors did not significantly increase discrimination, being 94%, and leaving only 4 predictors of the original model: sex, skin prick test, peanut sIgE, and total IgE minus sIgE. When building a model with sIgE to peanut components, Ara h 2 was the only predictor, with a discriminative ability of 90%. Cutoff values Conclusions: Discrimination of the validated model was good; however, calibration was poor. The discriminative ability of Ara h 2 was almost comparable to that of the updated model, containing 4 predictors. With both models, the need for peanut challenges could be reduced by at least 50%. (J Allergy Clin Immunol 2013;131:157-63.