Transcriptomic analysis reveals the molecular mechanisms underlying osteoclast differentiation in the estrogen-deficient pullets

Several previous reports have suggested that estrogen (E2) is a vital signal responsible for the reg-ulation of skeletal homeostasis and bone remodeling in mammals. E2 could efficiently accelerate the growth of medullary bone in pullets during sexual maturity. Fur-thermore, the low E2 level can strengthen the mechanical bone functions in female hens. However, mechanistic studies to describe the effects of E2 on bone in pullets during the initiation of the puberty period are remaining elusive. Therefore, the aim of this study was to explore the effect of inhibiting E2 biosynthesis on the biomechani-cal properties and its molecular mechanism during sexual maturity of pullets. In this study, a total of 90 Hy-line Sonia pullets with comparable body weight at 13 wk of age were selected and categorized into 2 separate groups. Daily, 0.5 mg/4 mL of letrozole (LZ) was orally adminis-tered to the treatment (TRT) group and 4 mL of saline to the control (CON) group of pullets for 6 wk. Com-pared with the CON group, a lower plasma E2 level was observed in the TRT group. Furthermore, plasma P, Gla protein (BGP), and 1,25-dihydroxy vitamin D3 (1,25-(OH)2D3) levels were markedly suppressed, whereas the plasma alkaline phosphatase (ALP) and tartrate-resistant acid phosphatase (TRAP) levels were signifi-cantly elevated. Moreover, the cortical bone thickness and breaking strength of the tibia and femur, the bone mineral density of the humerus, and the bone mineral content of the humerus as well as the femur were increased significantly. The expression levels of 340 dif-ferentially expressed genes (DEGs) differed signifi-cantly between the CON and TRT group in the tibia at 19 wk of age. Among them, 32 genes were up-regulated, whereas 308 were down-regulated in the TRT group. The variations in candidate genes associated with oste-oclast differentiation and cell adhesion may indicate that LZ inhibits E2 biosynthesis, consequently, reduces osteoclast differentiation by suppressing inter-cellular communication and cells attaching to extracellular matrix components. Taken together, the present study demonstrated that inhibiting E2 synthesis during sex-ual maturity of pullets decreased osteoclast differentia-tion and considerably enhanced bone quality

Development, test and comparison of two Multiple Criteria Decision Analysis(MCDA) models: A case of healthcare infrastructure location

When planning a new development, location decisions have always been a major issue. This paper examines and compares two modelling methods used to inform a healthcare infrastructure location decision. Two Multiple Criteria Decision Analysis (MCDA) models were developed to support the optimisation of this decision-making process, within a National Health Service (NHS) organisation, in the UK. The proposed model structure is based on seven criteria (environment and safety, size, total cost, accessibility, design, risks and population profile) and 28 sub-criteria. First, Evidential Reasoning (ER) was used to solve the model, then, the processes and results were compared with the Analytical Hierarchy Process (AHP). It was established that using ER or AHP led to the same solutions. However, the scores between the alternatives were significantly different; which impacted the stakeholders‟ decision-making. As the processes differ according to the model selected, ER or AHP, it is relevant to establish the practical and managerial implications for selecting one model or the other and providing evidence of which models best fit this specific environment. To achieve an optimum operational decision it is argued, in this study, that the most transparent and robust framework is achieved by merging ER process with the pair-wise comparison, an element of AHP. This paper makes a defined contribution by developing and examining the use of MCDA models, to rationalise new healthcare infrastructure location, with the proposed model to be used for future decision. Moreover, very few studies comparing different MCDA techniques were found, this study results enable practitioners to consider even further the modelling characteristics to ensure the development of a reliable framework, even if this means applying a hybrid approach

The Paf1 complex transcriptionally regulates the mitochondrial-anchored protein Atg32 leading to activation of mitophagy

Mitophagy is a critical process that safeguards mitochondrial quality control in order to maintain proper cellular homeostasis. Although the mitochondrial-anchored receptor Atg32-mediated cargo-recognition system has been well characterized to be essential for this process, the signaling pathway modulating its expression as a contribution of governing the mitophagy process remains largely unknown. Here, bioinformatics analyses of epigenetic or transcriptional regulators modulating gene expression allow us to identify the Paf1 complex (the polymerase-associated factor 1 complex, Paf1C,) as a transcriptional repressor of ATG genes. We show that Paf1C suppresses glucose starvation-induced autophagy, but does not affect nitrogen starvation- or rapamycin-induced autophagy. Moreover, we show that Paf1C specifically regulates mitophagy through modulating ATG32 expression. Deletion of the genes encoding two core subunits of Paf1C, Paf1 and Ctr9, increases ATG32 and ATG11 expression and facilitates mitophagy activity. Although Paf1C is required for many histone modifications and gene activation, we show that Paf1C regulates mitophagy independent of its positive regulatory role in other processes. More importantly, we also demonstrate the mitophagic role of PAF1C in mammals. Overall, we conclude that Paf1C maintains mitophagy at a low level through binding the promoter of the ATG32 gene in glucose-rich conditions. Dissociation of Paf1C from ATG32 leads to the increased expression of this gene, and mitophagy induction upon glucose starvation. Thus, we uncover a new role of Paf1C in modulating the mitophagy process at the transcriptional level

Genome-wide association and genomic prediction for resistance to southern corn rust in DH and testcross populations

Southern corn rust (SCR), caused by Puccinia polysora Underw, is a destructive disease that can severely reduce grain yield in maize (Zea mays L.). Owing to P. polysora being multi-racial, it is very important to explore more resistance genes and develop more efficient selection approaches in maize breeding programs. Here, four Doubled Haploid (DH) populations with 384 accessions originated from selected parents and their 903 testcross hybrids were used to perform genome-wide association (GWAS). Three GWAS processes included the additive model in the DH panel, additive and dominant models in the hybrid panel. As a result, five loci were detected on chromosomes 1, 7, 8, 8, and 10, with P-values ranging from 4.83×10-7 to 2.46×10-41. In all association analyses, a highly significant locus on chromosome 10 was detected, which was tight chained with the known SCR resistance gene RPPC and RPPK. Genomic prediction (GP), has been proven to be effective in plant breeding. In our study, several models were performed to explore predictive ability in hybrid populations for SCR resistance, including extended GBLUP with different genetic matrices, maker based prediction models, and mixed models with QTL as fixed factors. For GBLUP models, the prediction accuracies ranged from 0.56-0.60. Compared with traditional prediction only with additive effect, prediction ability was significantly improved by adding additive-by-additive effect (P-value< 0.05). For maker based models, the accuracy of BayesA and BayesB was 0.65, 8% higher than other models (i.e., RRBLUP, BRR, BL, BayesC). Finally, by adding QTL into the mixed linear prediction model, the accuracy can be further improved to 0.67, especially for the G_A model, the prediction performance can be increased by 11.67%. The prediction accuracy of the BayesB model can be further improved significantly by adding QTL information (P-value< 0.05). This study will provide important valuable information for understanding the genetic architecture and the application of GP for SCR in maize breeding

A novel class of microRNA-recognition elements that function only within open reading frames.

MicroRNAs (miRNAs) are well known to target 3' untranslated regions (3' UTRs) in mRNAs, thereby silencing gene expression at the post-transcriptional level. Multiple reports have also indicated the ability of miRNAs to target protein-coding sequences (CDS); however, miRNAs have been generally believed to function through similar mechanisms regardless of the locations of their sites of action. Here, we report a class of miRNA-recognition elements (MREs) that function exclusively in CDS regions. Through functional and mechanistic characterization of these 'unusual' MREs, we demonstrate that CDS-targeted miRNAs require extensive base-pairing at the 3' side rather than the 5' seed; cause gene silencing in an Argonaute-dependent but GW182-independent manner; and repress translation by inducing transient ribosome stalling instead of mRNA destabilization. These findings reveal distinct mechanisms and functional consequences of miRNAs that target CDS versus the 3' UTR and suggest that CDS-targeted miRNAs may use a translational quality-control-related mechanism to regulate translation in mammalian cells

Including cognitive aspects in multiple criteria decision analysis

"First Online: 21 December 2016"Many Multiple Criteria Decision Analysis (MCDA) methods have been proposed over the last decades. Some of the most known methods share some similarities in the way they are used and configured. However, we live in a time of change and nowadays the decision-making process (especially when done in group) is even more demanding and dynamic. In this work, we propose a Multiple Criteria Decision Analysis method that includes cognitive aspects (Cognitive Analytic Process). By taking advantage of aspects such as expertise level, credibility and behaviour style of the decision-makers, we propose a method that relates these aspects with problem configurations (alternatives and criteria preferences) done by each decision-maker. In this work, we evaluated the Cognitive Analytic Process (CAP) in terms of configuration costs and the capability to enhance the quality of the decision. We have used the satisfaction level as a metric to compare our method with other known MCDA methods in literature (Utility function, AHP and TOPSIS). Our method proved to be capable to achieve higher satisfaction levels compared to other MCDA methods, especially when the decision suggested by CAP is different from the one proposed by those methods.This work was supported by COMPETE Programme (operational programme for competitiveness) within project POCI-01-0145-FEDER-007043, by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UID/CEC/00319/2013, UID/EEA/00760/2013, and the João Carneiro PhD grant with the reference SFRH/BD/89697/2012.info:eu-repo/semantics/publishedVersio

Cdx4 and Menin Co-Regulate Hoxa9 Expression in Hematopoietic Cells

BACKGROUND: Transcription factor Cdx4 and transcriptional coregulator menin are essential for Hoxa9 expression and normal hematopoiesis. However, the precise mechanism underlying Hoxa9 regulation is not clear. METHODS AND FINDINGS: Here, we show that the expression level of Hoxa9 is correlated with the location of increased trimethylated histone 3 lysine 4 (H3K4M3). The active and repressive histone modifications co-exist along the Hoxa9 regulatory region. We further demonstrate that both Cdx4 and menin bind to the same regulatory region at the Hoxa9 locus in vivo, and co-activate the reporter gene driven by the Hoxa9 cis-elements that contain Cdx4 binding sites. Ablation of menin abrogates Cdx4 access to the chromatin target and significantly reduces both active and repressive histone H3 modifications in the Hoxa9 locus. CONCLUSION: These results suggest a functional link among Cdx4, menin and histone modifications in Hoxa9 regulation in hematopoietic cells

Classifying RNA-Binding Proteins Based on Electrostatic Properties

Protein structure can provide new insight into the biological function of a protein and can enable the design of better experiments to learn its biological roles. Moreover, deciphering the interactions of a protein with other molecules can contribute to the understanding of the protein's function within cellular processes. In this study, we apply a machine learning approach for classifying RNA-binding proteins based on their three-dimensional structures. The method is based on characterizing unique properties of electrostatic patches on the protein surface. Using an ensemble of general protein features and specific properties extracted from the electrostatic patches, we have trained a support vector machine (SVM) to distinguish RNA-binding proteins from other positively charged proteins that do not bind nucleic acids. Specifically, the method was applied on proteins possessing the RNA recognition motif (RRM) and successfully classified RNA-binding proteins from RRM domains involved in protein–protein interactions. Overall the method achieves 88% accuracy in classifying RNA-binding proteins, yet it cannot distinguish RNA from DNA binding proteins. Nevertheless, by applying a multiclass SVM approach we were able to classify the RNA-binding proteins based on their RNA targets, specifically, whether they bind a ribosomal RNA (rRNA), a transfer RNA (tRNA), or messenger RNA (mRNA). Finally, we present here an innovative approach that does not rely on sequence or structural homology and could be applied to identify novel RNA-binding proteins with unique folds and/or binding motifs

H3 Lysine 4 Is Acetylated at Active Gene Promoters and Is Regulated by H3 Lysine 4 Methylation

Methylation of histone H3 lysine 4 (H3K4me) is an evolutionarily conserved modification whose role in the regulation of gene expression has been extensively studied. In contrast, the function of H3K4 acetylation (H3K4ac) has received little attention because of a lack of tools to separate its function from that of H3K4me. Here we show that, in addition to being methylated, H3K4 is also acetylated in budding yeast. Genetic studies reveal that the histone acetyltransferases (HATs) Gcn5 and Rtt109 contribute to H3K4 acetylation in vivo. Whilst removal of H3K4ac from euchromatin mainly requires the histone deacetylase (HDAC) Hst1, Sir2 is needed for H3K4 deacetylation in heterochomatin. Using genome-wide chromatin immunoprecipitation (ChIP), we show that H3K4ac is enriched at promoters of actively transcribed genes and located just upstream of H3K4 tri-methylation (H3K4me3), a pattern that has been conserved in human cells. We find that the Set1-containing complex (COMPASS), which promotes H3K4me2 and -me3, also serves to limit the abundance of H3K4ac at gene promoters. In addition, we identify a group of genes that have high levels of H3K4ac in their promoters and are inadequately expressed in H3-K4R, but not in set1Δ mutant strains, suggesting that H3K4ac plays a positive role in transcription. Our results reveal a novel regulatory feature of promoter-proximal chromatin, involving mutually exclusive histone modifications of the same histone residue (H3K4ac and H3K4me)

Interaction of SET domains with histones and nucleic acid structures in active chromatin

Changes in the normal program of gene expression are the basis for a number of human diseases. Epigenetic control of gene expression is programmed by chromatin modifications—the inheritable “histone code”—the major component of which is histone methylation. This chromatin methylation code of gene activity is created upon cell differentiation and is further controlled by the “SET” (methyltransferase) domain proteins which maintain this histone methylation pattern and preserve it through rounds of cell division. The molecular principles of epigenetic gene maintenance are essential for proper treatment and prevention of disorders and their complications. However, the principles of epigenetic gene programming are not resolved. Here we discuss some evidence of how the SET proteins determine the required states of target genes and maintain the required levels of their activity. We suggest that, along with other recognition pathways, SET domains can directly recognize the nucleosome and nucleic acids intermediates that are specific for active chromatin regions