RESULTS: The chloroplast genome of Gracilaria firma maps as a circular molecule of 187,001 bp and contains 252 genes, which are distributed on both strands and consist of 35 RNA genes (3 rRNAs, 30 tRNAs, tmRNA and a ribonuclease P RNA component) and 217 protein-coding genes, including the unidentified open reading frames. The chloroplast genome of G. firma is by far the largest reported for Gracilariaceae, featuring a unique intergenic region of about 7000 bp with discontinuous vestiges of red algal plasmid DNA sequences interspersed between the nblA and cpeB genes. This chloroplast genome shows similar gene content and order to other Florideophycean taxa. Phylogenomic analyses based on the concatenated amino acid sequences of 146 protein-coding genes confirmed the monophyly of the classes Bangiophyceae and Florideophyceae with full nodal support. Relationships within the subclass Rhodymeniophycidae in Florideophyceae received moderate to strong nodal support, and the monotypic family of Gracilariales were resolved with maximum support.
CONCLUSIONS: Chloroplast genomes hold substantial information that can be tapped for resolving the phylogenetic relationships of difficult regions in the Rhodymeniophycidae, which are perceived to have experienced rapid radiation and thus received low nodal support, as exemplified in this study. The present study shows that chloroplast genome of G. firma could serve as a key link to the full resolution of Gracilaria sensu lato complex and recognition of Hydropuntia as a genus distinct from Gracilaria sensu stricto.
METHODS: DNA methylation profiles (Illumina Infinium® HumanMethylation450 BeadChip) from 1941 individuals from four population-based European cohorts were analysed in relation to body mass index, waist circumference, waist-hip and waist-height ratio within a meta-analytical framework. In a subset of these individuals, data on genome-wide gene expression level, biomarkers of glucose and lipid metabolism were also available. Validation of methylation markers associated with all adiposity measures was performed in 358 individuals. Finally, we investigated the association of obesity-related methylation marks with breast, colorectal cancer and myocardial infarction within relevant subsets of the discovery population.
RESULTS: We identified 40 CpG loci with methylation levels associated with at least one adiposity measure. Of these, one CpG locus (cg06500161) in ABCG1 was associated with all four adiposity measures (P = 9.07×10-8 to 3.27×10-18) and lower transcriptional activity of the full-length isoform of ABCG1 (P = 6.00×10-7), higher triglyceride levels (P = 5.37×10-9) and higher triglycerides-to-HDL cholesterol ratio (P = 1.03×10-10). Of the 40 informative and obesity-related CpG loci, two (in IL2RB and FGF18) were significantly associated with colorectal cancer (inversely, P
METHODOLOGY: A total of 102 FFPE cervical tissues were collected from 2 tertiary hospitals and immunohistochemical reactivity staining of E6 and E7 oncoproteins of HPV16 and HPV18 were evaluated using immunoreactive scoring (IRS) system and analysed statistically.
RESULT: The result showed an increased oncoprotein expression with the progression of cervical lesions. There is a statistically significant association between histology grade and HPV16/18-E6 expression (p = 0.028). However, there are no significant association of histological grade to HPV16-E7 immunoreactivity score (p = 0.264) and HPV18-E7 (p=0.080).
CONCLUSION: The immunohistochemical expression of HPV oncoproteins is a potential alternative diagnostic tool applicable in a low-resource laboratory setting. The advantage of the histochemical evaluation is that this method is simpler to apply and less expensive in comparison to in situ mRNA hybridization. Nevertheless, our study also found that antibodies against HPV that are commercially available suffer quite substantial specificity issues such as background staining and inconsistency between different batches. Hence, the utilization of antibody-based staining warrants stringent quality control.
RESULTS: In this study, we propose the Context Based Dependency Network (CBDN), a method that is able to infer gene regulatory networks with the regulatory directions from gene expression data only. To determine the regulatory direction, CBDN computes the influence of source to target by evaluating the magnitude changes of expression dependencies between the target gene and the others with conditioning on the source gene. CBDN extends the data processing inequality by involving the dependency direction to distinguish between direct and transitive relationship between genes. We also define two types of important regulators which can influence a majority of the genes in the network directly or indirectly. CBDN can detect both of these two types of important regulators by averaging the influence functions of candidate regulator to the other genes. In our experiments with simulated and real data, even with the regulatory direction taken into account, CBDN outperforms the state-of-the-art approaches for inferring gene regulatory network. CBDN identifies the important regulators in the predicted network: 1. TYROBP influences a batch of genes that are related to Alzheimer's disease; 2. ZNF329 and RB1 significantly regulate those 'mesenchymal' gene expression signature genes for brain tumors.
CONCLUSION: By merely leveraging gene expression data, CBDN can efficiently infer the existence of gene-gene interactions as well as their regulatory directions. The constructed networks are helpful in the identification of important regulators for complex diseases.