BackgroundBombyx mori was domesticated from the Chinese wild silkworm, Bombyx mandarina. Wild and domestic silkworms are good models in which to investigate genes related to silk protein synthesis that may be differentially expressed in silk glands, because their silk productions are very different. Here we used the mRNA deep sequencing (RNA-seq) approach to identify the differentially expressed genes (DEGs) in the transcriptomes of the median/posterior silk glands of two domestic and two wild silkworms.ResultsThe results indicated that about 58% of the total genes were expressed (reads per kilo bases per million reads (RPKM) ≥ 1) in each silkworm. Comparisons of the domestic and wild silkworm transcriptomes revealed 32 DEGs, of which 16 were up-regulated in the domestic silkworms compared with in the wild silkworms, and the other 16 were up-regulated in the wild silkworms compared with in the domestic silkworms. Quantitative real-time polymerase chain reaction (qPCR) was performed for 15 randomly selected DEGs in domestic versus wild silkworms. The qPCR results were mostly consistent with the expression levels determined from the RNA-seq data. Based on a Gene Ontology (GO) enrichment analysis and manual annotation, five of the up-regulated DEGs in the wild silkworms were predicted to be involved in immune response, and seven of the up-regulated DEGs were related to the GO term “oxidoreductase activity”, which is associated with antioxidant systems. In the domestic silkworms, the up-regulated DEGs were related mainly to tissue development, secretion of proteins and metabolism.ConclusionsThe up-regulated DEGs in the two domestic silkworms may be involved mainly in the highly efficient biosynthesis and secretion of silk proteins, while the up-regulated DEGs in the two wild silkworms may play more important roles in tolerance to pathogens and environment adaptation. Our results provide a foundation for understanding the molecular mechanisms of the silk production difference between domestic and wild silkworms.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1287-9) contains supplementary material, which is available to authorized users.
Chronic disruptive behaviors during early childhood are associated with many poor developmental outcomes including, but not limited to, school dropout and conduct disorder during adolescence. Much is known regarding effective intervention procedures for disruptive classroom behaviors by preschool children. Unfortunately, evidence-based intervention procedures may not be implemented with integrity in applied settings. Direct behavioral consultation may increase teacher intervention integrity because of direct training procedures used with teachers and students during routine classroom activities. This study evaluated a nondisruptive direct training method for increasing Head Start teachers' use of praise and effective instruction delivery. Results indicated that the direct training procedure implemented during routine instructional activities resulted in increased use of praise and effective instruction delivery that maintained following training. Additionally, increased use of praise and effective instruction delivery resulted in reductions in children's disruptive classroom behavior.The prevalence of disruptive behavior disorders in preschool and early school-age children is approximately 10% and may be as high as 25% forCorrespondence should be sent to Brad A. Dufrene,
Spatial transcriptomics has been emerging as a powerful technique for resolving gene expression profiles while retaining tissue spatial information. These spatially resolved transcriptomics make it feasible to examine the complex multicellular systems of different microenvironments. To answer scientific questions with spatial transcriptomics and expand our understanding of how cell types and states are regulated by microenvironment, the first step is to identify cell clusters by integrating the available spatial information. Here, we introduce SC-MEB, an empirical Bayes approach for spatial clustering analysis using a hidden Markov random field. We have also derived an efficient expectation-maximization algorithm based on an iterative conditional mode for SC-MEB. In contrast to BayesSpace, a recently developed method, SC-MEB is not only computationally efficient and scalable to large sample sizes but is also capable of choosing the smoothness parameter and the number of clusters. We performed comprehensive simulation studies to demonstrate the superiority of SC-MEB over some existing methods. We applied SC-MEB to analyze the spatial transcriptome of human dorsolateral prefrontal cortex tissues and mouse hypothalamic preoptic region. Our analysis results showed that SC-MEB can achieve a similar or better clustering performance to BayesSpace, which uses the true number of clusters and a fixed smoothness parameter. Moreover, SC-MEB is scalable to large ‘sample sizes’. We then employed SC-MEB to analyze a colon dataset from a patient with colorectal cancer (CRC) and COVID-19, and further performed differential expression analysis to identify signature genes related to the clustering results. The heatmap of identified signature genes showed that the clusters identified using SC-MEB were more separable than those obtained with BayesSpace. Using pathway analysis, we identified three immune-related clusters, and in a further comparison, found the mean expression of COVID-19 signature genes was greater in immune than non-immune regions of colon tissue. SC-MEB provides a valuable computational tool for investigating the structural organizations of tissues from spatial transcriptomic data.
Background:Marrow adipose tissue (MAT) has been shown to be vital for regulating metabolism and maintaining skeletal homeostasis in the bone marrow (BM) niche. As a reflection of BM remodeling, MAT is highly responsive to nutrient fluctuations, hormonal changes, and metabolic disturbances such as obesity and diabetes mellitus. Expansion of MAT has also been strongly associated with bone loss in mice and humans. However, the regulation of BM plasticity remains poorly understood, as does the mechanism that links changes in marrow adiposity with bone remodeling.Methods:We studied deletion of Adipsin, and its downstream effector, C3, in C57BL/6 mice as well as the bone-protected PPARγ constitutive deacetylation 2KR mice to assess BM plasticity. The mice were challenged with thiazolidinedione treatment, calorie restriction, or aging to induce bone loss and MAT expansion. Analysis of bone mineral density and marrow adiposity was performed using a μCT scanner and by RNA analysis to assess adipocyte and osteoblast markers. For in vitro studies, primary bone marrow stromal cells were isolated and subjected to osteoblastogenic or adipogenic differentiation or chemical treatment followed by morphological and molecular analyses. Clinical data was obtained from samples of a previous clinical trial of fasting and high-calorie diet in healthy human volunteers.Results:We show that Adipsin is the most upregulated adipokine during MAT expansion in mice and humans in a PPARγ acetylation-dependent manner. Genetic ablation of Adipsin in mice specifically inhibited MAT expansion but not peripheral adipose depots, and improved bone mass during calorie restriction, thiazolidinedione treatment, and aging. These effects were mediated through its downstream effector, complement component C3, to prime common progenitor cells toward adipogenesis rather than osteoblastogenesis through inhibiting Wnt/β-catenin signaling.Conclusions:Adipsin promotes new adipocyte formation and affects skeletal remodeling in the BM niche. Our study reveals a novel mechanism whereby the BM sustains its own plasticity through paracrine and endocrine actions of a unique adipokine.Funding:This work was supported by the National Institutes of Health T32DK007328 (NA), F31DK124926 (NA), R01DK121140 (JCL), R01AR068970 (BZ), R01AR071463 (BZ), R01DK112943 (LQ), R24DK092759 (CJR), and P01HL087123 (LQ).
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