The CCAAT/enhancer binding protein delta (CEBPD, C/EBPδ, NF-IL6β) is induced in many inflammation-related diseases, suggesting that CEBPD and its downstream targets may play central roles in these conditions. Neuropathological studies show that a neuroinflammatory response parallels the early stages of Alzheimer's disease (AD). However, the precise mechanistic correlation between inflammation and AD pathogenesis remains unclear. CEBPD is upregulated in the astrocytes of AD patients. Therefore, we asked if activation of astrocytic CEBPD could contribute to AD pathogenesis. In this report, a novel role of CEBPD in attenuating macrophage-mediated phagocytosis of damaged neuron cells was found. By global gene expression profiling, we identified the inflammatory marker pentraxin-3 (PTX3, TNFAIP5, TSG-14) as a CEBPD target in astrocytes. Furthermore, we demonstrate that PTX3 participates in the attenuation of macrophage-mediated phagocytosis of damaged neuron cells. This study provides the first demonstration of a role for astrocytic CEBPD and the CEBPD-regulated molecule PTX3 in the accumulation of damaged neurons, which is a hallmark of AD pathogenesis.

BackgroundHepatitis B virus (HBV) quasispecies are crucial in the pathogenesis of chronic liver disease. Next-generation sequencing (NGS) is powerful for identifying viral quasispecies. To improve mapping quality and single nucleotide variant (SNV) calling accuracy in the NGS analysis of HBV, we compared different mapping references, including the sample-specific reference sequence, same genotype sequences and different genotype sequences, according to the sample.MethodsReal Illumina HBV datasets from 86 patients, and simulated datasets from 158 HBV strains in the GenBank database, were used to assess mapping quality. SNV calling accuracy was evaluated using different mapping references to align Real Illumina datasets from a single HBV clone.ResultsUsing the sample-specific reference sequence as a mapping reference produced the largest number of mappable reads and coverages. With a different genotype mapping reference, the consensus sequence derived from the Real Illumina datasets of the single HBV clone showed 21 false SNV callings in polymerase and surface genes, the regions most divergent between the mapping reference and this HBV clone. A ~6 % coverage of most of these false SNVs was yielded even with a same genotype mapping reference, but none with the sample-specific reference sequence.ConclusionsUsing sample-specific reference sequences as a mapping reference in NGS analysis optimized mapping quality and the SNV calling accuracy for HBV quasispecies.Electronic supplementary materialThe online version of this article (doi:10.1007/s12072-015-9645-x) contains supplementary material, which is available to authorized users.

In the actual case study of this research, REMMAR utilized the shortest distance between any two genes in the Saccharomyces cerevisiae gene regulatory network (GRN) as the relation intensity to discover the association rules from two S.cerevisiae gene expression datasets. Under experimental evaluation, REMMAR can generate more rules with stronger relation intensity, and filter out rules without biological meaning in the protein-protein interaction network (PPIN). Furthermore, the proposed method has a higher precision (100%) than the precision of reference Apriori method (87.5%) for the discovered rules use a literature survey. Therefore, the proposed REMMAR algorithm can discover stronger association rules in biological relationships dissimilated by traditional methods to assist biologists in complicated genetic exploration.

We present a new analysis framework, using ESCC progression-associated gene regulatory network (GRN escc), to identify differentially methylated CpG sites prognostic of ESCC progression. From the CpG loci differentially methylated in 50 tumor-normal pairs, we selected 44 CpG loci most highly associated with survival and located in the promoters of genes more likely to belong to GRN escc. Using an independent ESCC cohort, we confirmed that 8/10 of CpG loci in the promoter of GRN escc genes significantly correlated with patient survival. In contrast, 0/10 CpG loci in the promoter genes outside the GRN escc were correlated with patient survival. We further characterized the GRN escc network topology and observed that the genes with methylated CpG loci associated with survival deviated from the center of mass and were less likely to be hubs in the GRN escc. We postulate that our analysis framework improves the identification of bona fide prognostic biomarkers from DNA methylation studies, especially with partial genome coverage.