Genomic Relatedness Strengthens Genetic Connectedness Across Management Units

Genetic connectedness refers to a measure of genetic relatedness across management units (e.g., herds and flocks). With the presence of high genetic connectedness in management units, best linear unbiased prediction (BLUP) is known to provide reliable comparisons between estimated genetic values. Genetic connectedness has been studied for pedigree-based BLUP; however, relatively little attention has been paid to using genomic information to measure connectedness. In this study, we assessed genomebased connectedness across management units by applying prediction error variance of difference (PEVD), coefficient of determination (CD), and prediction error correlation r to a combination of computer simulation and real data (mice and cattle). We found that genomic information (G) increased the estimate of connectedness among individuals from different management units compared to that based on pedigree (A). A disconnected design benefited the most. In both datasets, PEVD and CD statistics inferred increased connectedness across units when using G- rather than A-based relatedness, suggesting stronger connectedness. With r once using allele frequencies equal to one-half or scaling G to values between 0 and 2, which is intrinsic to A; connectedness also increased with genomic information. However, PEVD occasionally increased, and r decreased when obtained using the alternative form of G; instead suggesting less connectedness. Such inconsistencies were not found with CD. We contend that genomic relatedness strengthens measures of genetic connectedness across units and has the potential to aid genomic evaluation of livestock species

Do stronger measures of genomic connectedness enhance prediction accuracies across management units?

Genetic connectedness assesses the extent to which estimated breeding values can be fairly compared across management units. Ranking of individuals across units based on best linear unbiased prediction (BLUP) is reliable when there is a sufficient level of connectedness due to a better disentangling of genetic signal from noise. Connectedness arises from genetic relationships among individuals. Although a recent study showed that genomic relatedness strengthens the estimates of connectedness across management units compared with that of pedigree, the relationship between connectedness measures and prediction accuracies only has been explored to a limited extent. In this study, we examined whether increased measures of connectedness led to higher prediction accuracies evaluated by a cross-validation (CV) based on computer simulations. We applied prediction error variance of the difference, coefficient of determination (CD), and BLUP-type prediction models to data simulated under various scenarios. We found that a greater extent of connectedness enhanced accuracy of whole-genome prediction. The impact of genomics was more marked when large numbers of markers were used to infer connectedness and evaluate prediction accuracy. Connectedness across units increased with the proportion of connecting individuals and this increase was associated with improved accuracy of prediction. The use of genomic information resulted in increased estimates of connectedness and improved prediction accuracies compared with those of pedigree-based models when there were enough markers to capture variation due to QTL signals

Element-resolved x-ray ferrimagnetic and ferromagnetic resonance spectroscopy

We report on the measurement of element-specific magnetic resonance spectra at gigahertz frequencies using x-ray magnetic circular dichroism (XMCD). We investigate the ferrimagnetic precession of Gd and Fe ions in Gd-substituted Yttrium Iron Garnet, showing that the resonant field and linewidth of Gd precisely coincide with Fe up to the nonlinear regime of parametric excitations. The opposite sign of the Gd x-ray magnetic resonance signal with respect to Fe is consistent with dynamic antiferromagnetic alignment of the two ionic species. Further, we investigate a bilayer metal film, Ni$_{80}$Fe$_{20}$(5 nm)/Ni(50 nm), where the coupled resonance modes of Ni and Ni$_{80}$Fe$_{20}$ are separately resolved, revealing shifts in the resonance fields of individual layers but no mutual driving effects. Energy-dependent dynamic XMCD measurements are introduced, combining x-ray absorption and magnetic resonance spectroscopies.Comment: 16 pages, 8 figure

Depth video data-enabled predictions of longitudinal dairy cow body weight using thresholding and Mask R-CNN algorithms

Monitoring cow body weight is crucial to support farm management decisions due to its direct relationship with the growth, nutritional status, and health of dairy cows. Cow body weight is a repeated trait, however, the majority of previous body weight prediction research only used data collected at a single point in time. Furthermore, the utility of deep learning-based segmentation for body weight prediction using videos remains unanswered. Therefore, the objectives of this study were to predict cow body weight from repeatedly measured video data, to compare the performance of the thresholding and Mask R-CNN deep learning approaches, to evaluate the predictive ability of body weight regression models, and to promote open science in the animal science community by releasing the source code for video-based body weight prediction. A total of 40,405 depth images and depth map files were obtained from 10 lactating Holstein cows and 2 non-lactating Jersey cows. Three approaches were investigated to segment the cow's body from the background, including single thresholding, adaptive thresholding, and Mask R-CNN. Four image-derived biometric features, such as dorsal length, abdominal width, height, and volume, were estimated from the segmented images. On average, the Mask-RCNN approach combined with a linear mixed model resulted in the best prediction coefficient of determination and mean absolute percentage error of 0.98 and 2.03%, respectively, in the forecasting cross-validation. The Mask-RCNN approach was also the best in the leave-three-cows-out cross-validation. The prediction coefficients of determination and mean absolute percentage error of the Mask-RCNN coupled with the linear mixed model were 0.90 and 4.70%, respectively. Our results suggest that deep learning-based segmentation improves the prediction performance of cow body weight from longitudinal depth video data

Predictive ability of genome-assisted statistical models under various forms of gene action

Recent work has suggested that the performance of prediction models for complex traits may depend on the architecture of the target traits. Here we compared several prediction models with respect to their ability of predicting phenotypes under various statistical architectures of gene action: (1) purely additive, (2) additive and dominance, (3) additive, dominance, and two-locus epistasis, and (4) purely epistatic settings. Simulation and a real chicken dataset were used. Fourteen prediction models were compared: BayesA, BayesB, BayesC, Bayesian LASSO, Bayesian ridge regression, elastic net, genomic best linear unbiased prediction, a Gaussian process, LASSO, random forests, reproducing kernel Hilbert spaces regression, ridge regression (best linear unbiased prediction), relevance vector machines, and support vector machines. When the trait was under additive gene action, the parametric prediction models outperformed non-parametric ones. Conversely, when the trait was under epistatic gene action, the non-parametric prediction models provided more accurate predictions. Thus, prediction models must be selected according to the most probably underlying architecture of traits. In the chicken dataset examined, most models had similar prediction performance. Our results corroborate the view that there is no universally best prediction models, and that the development of robust prediction models is an important research objective

APROXIMAÇÕES ENTRE A AGRICULTURA FAMILIAR E O TURISMO NO MUNICÍPIO DE INHAMBANE EM MOÇAMBIQUE

Tourism is a socio-economic activity that also needs agriculture for the development of its activities. Thus, it is assumed that communities and especially small farmers benefit directly from tourism and improve the quality of your life. This study was conducted in order to analyze the type of agricultural products produced by households and those acquired/demanded by managers of tourist establishments, seeking to understand the relations between the two economic sectors. In spatial terms, the study was conducted on the beaches of Tofo and Barra and in the urban area of ​​ municipality of Inhambane.  For data collection, a total of 185 households and 45 tourist establishments were selected using a random sampling, which were submitted to a questionnaire that was analyzed using descriptive statistics. The results of this research show that tourist establishments acquire among farmers, fruit and vegetables, such as orange, papaya, banana and lettuce, collard green, cabbage and tomatoes. However, besides producing vegetables, farmers practice rain-fed agriculture, providing products that can be purchased by tourist establishments. The results show that the purchases made by tourist establishments influence the local agricultural production and contribute to link tourism and agriculture in municipality Inhambane. It was also that there are basic conditions for increasing agricultural production to the needs of tourism establishment’s managers, which could improve income, food sovereignty, nutrition and quality of life in general of all the inhabitants of this municipality.O turismo é uma atividade sócio-económica que necessita da agricultura, igualmente, para o desenvolvimento das suas atividades. Assim, pressupõe-se que as comunidades e principalmente os pequenos agricultores beneficiam-se diretamente da atividade turística e melhoram a qualidade de sua vida. O presente estudo foi conduzido com objetivo de analisar o tipo de produtos agrícolas produzidos pelos agregados familiares e aqueles que são adquiridos/demandados pelos gestores de estabelecimentos turísticos, buscando entender às relações estabelecidas entre os dois sectores económicos. Em termos espaciais, o estudo foi conduzido nas praias de Tofo e Barra e na área urbana do município de Inhambane. Para coleta de dados, um total de 185 agregados familiares e 45 estabelecimentos turísticos foram selecionados usando uma amostragem probabilística, os quais foram submetidos a um questionário que foi analisado através da estatística descritiva. Os resultados desta pesquisa mostram que os estabelecimentos turísticos adquirem, junto dos agricultores familiares, frutas e hortícolas, tais como laranja, papaia, banana e alface, couve, repolho e tomate. Entretanto, além de produzirem hortícolas, os agricultores praticam a agricultura de sequeiro, disponibilizando produtos passíveis de serem adquiridos pelos estabelecimentos turísticos. Os resultados apontam que as compras efetuadas por estabelecimentos turísticos influenciam na produção agrícola local e estreitam a ligação entre o turismo e a agricultura no município de Inhambane. Verificou-se, igualmente, que existem condições básicas para aumentar a produção agrícola em função das necessidades dos gestores de estabelecimentos turísticos, facto que poderá melhorar a renda, a soberania alimentar, a nutrição e qualidade de vida em termos gerais de todos os habitantes deste município

Suppressed Magnetization at the Surfaces and Interfaces of Ferromagnetic Metallic Manganites

What happens to ferromagnetism at the surfaces and interfaces of manganites? With the competition between charge, spin, and orbital degrees of freedom, it is not surprising that the surface behavior may be profoundly different than that of the bulk. Using a powerful combination of two surface probes, tunneling and polarized x-ray interactions, this paper reviews our work on the nature of the electronic and magnetic states at manganite surfaces and interfaces. The general observation is that ferromagnetism is not the lowest energy state at the surface or interface, which results in a suppression or even loss of ferromagnetic order at the surface. Two cases will be discussed ranging from the surface of the quasi-2D bilayer manganite (La$_{2-2x}$Sr$_{1+2x}$Mn$_2$O$_7$) to the 3D Perovskite (La$_{2/3}$Sr$_{1/3}$MnO$_3$)/SrTiO$_3$ interface. For the bilayer manganite, that is, ferromagnetic and conducting in the bulk, these probes present clear evidence for an intrinsic insulating non-ferromagnetic surface layer atop adjacent subsurface layers that display the full bulk magnetization. This abrupt intrinsic magnetic interface is attributed to the weak inter-bilayer coupling native to these quasi-two-dimensional materials. This is in marked contrast to the non-layered manganite system (La$_{2/3}$Sr$_{1/3}$MnO$_3$/SrTiO$_3$), whose magnetization near the interface is less than half the bulk value at low temperatures and decreases with increasing temperature at a faster rate than the bulk.Comment: 15 pages, 13 figure

Intracellular temperature mapping with a fluorescent polymeric thermometer and fluorescence lifetime imaging microscopy

Cellular functions are fundamentally regulated by intracellular temperature, which influences biochemical reactions inside a cell. Despite the important contributions to biological and medical applications that it would offer, intracellular temperature mapping has not been achieved. Here we demonstrate the first intracellular temperature mapping based on a fluorescent polymeric thermometer and fluorescence lifetime imaging microscopy. The spatial and temperature resolutions of our thermometry were at the diffraction limited level (200 nm) and 0.18–0.58 °C. The intracellular temperature distribution we observed indicated that the nucleus and centrosome of a COS7 cell, both showed a significantly higher temperature than the cytoplasm and that the temperature gap between the nucleus and the cytoplasm differed depending on the cell cycle. The heat production from mitochondria was also observed as a proximal local temperature increase. These results showed that our new intracellular thermometry could determine an intrinsic relationship between the temperature and organelle function