Elemental concentrations in the seed of mutants and natural variants of Arabidopsis thaliana grown under varying soil conditions

Peer reviewedPublisher PD

High post-anthesis temperature effects on 3 bread wheat (Triticum aestivum L.) grain 4 transcriptome during early grain-filling

Background: High post-anthesis (p.a) temperatures reduce mature grain weights in wheat and other cereals. However, the causes of this reduction are not entirely known. Control of grain expansion by the maternally derived pericarp of the grain has previously been suggested, although this interaction has not been investigated under high p.a. temperatures. Down-regulation of pericarp localised genes that regulate cell wall expansion under high p.a. temperatures may limit expansion of the encapsulated endosperm due to a loss of plasticity in the pericarp,reducing mature grain weight. Here the effect of high p.a. temperatures on the transcriptome of the pericarp and endosperm of the wheat grain during early grain-filling was investigated via RNA-Seq and is discussed alongside grain moisture dynamics during early grain development and mature grain weight. Results: High p.a. temperatures applied from 6-days after anthesis (daa) and until 18daa reduced the grain’s ability to accumulate water, with total grain moisture and percentage grain moisture content being significantly reduced from 14daa onwards. Mature grain weight was also significantly reduced by the same high p.a. temperatures applied from 6daa for 4-days or more, in a separate experiment. Comparison of our RNA-Seq data from whole grains, with existing data sets from isolated pericarp and endosperm tissues enabled the identification of subsets of genes whose expression was significantly affected by high p.a. temperature and predominantly expressed in either tissue. Hierarchical clustering and gene ontology analysis resulted in the identification of a number of genes implicated in the regulation of cell wall expansion, predominantly expressed in the pericarp and significantly down26 regulated under high p.a. temperatures, including endoglucanase, xyloglucan endotransglycosylases and a β27 expansin. An over-representation of genes involved in the ‘cuticle development’ functional pathway that were expressed in the pericarp and affected by high p.a. temperatures was also observed. Conclusions: High p.a. temperature induced down-regulation of genes involved in regulating pericarp cell wall expansion. This concomitant down-regulation with a reduction in total grain moisture content and grain weight following the same treatment period, adds support to the theory that high p.a. temperatures may cause a reduction in mature grain weight as result of decreased pericarp cell wall expansion

Linking genes to diseases: it's all in the data

Genome-wide association analyses on large patient cohorts are generating large sets of candidate disease genes. This is coupled with the availability of ever-increasing genomic databases and a rapidly expanding repository of biomedical literature. Computational approaches to disease-gene association attempt to harness these data sources to identify the most likely disease gene candidates for further empirical analysis by translational researchers, resulting in efficient identification of genes of diagnostic, prognostic and therapeutic value. Existing computational methods analyze gene structure and sequence, functional annotation of candidate genes, characteristics of known disease genes, gene regulatory networks, protein-protein interactions, data from animal models and disease phenotype. To date, a few studies have successfully applied computational analysis of clinical phenotype data for specific diseases and shown genetic associations. In the near future, computational strategies will be facilitated by improved integration of clinical and computational research, and by increased availability of clinical phenotype data in a format accessible to computational approaches

Viral expression and molecular profiling in liver tissue versus microdissected hepatocytes in hepatitis B virus - associated hepatocellular carcinoma.

Background: The molecular mechanisms whereby hepatitis B virus (HBV) induces hepatocellular carcinoma (HCC) remain elusive. We used genomic and molecular techniques to investigate host-virus interactions by studying multiple areas of the same liver from patients with HCC. Methods: We compared the gene signature of whole liver tissue (WLT) versus laser capture-microdissected (LCM) hepatocytes along with the intrahepatic expression of HBV. Gene expression profiling was performed on up to 17 WLT specimens obtained at various distances from the tumor center from individual livers of 11 patients with HCC and on selected LCM samples. HBV markers in liver and serum were determined by real-time polymerase chain reaction (PCR)and confocal immunofluorescence. Results: Analysis of 5 areas of the liver showed a sharp change in gene expression between the immediate perilesional area and tumor periphery that correlated with a significant decrease in the intrahepatic expression of HB surface antigen (HBsAg). The tumor was characterized by a large preponderance of down-regulated genes, mostly involved in the metabolism of lipids and fatty acids, glucose, amino acids and drugs, with down-regulation of pathways involved in the activation of PXR/RXR and PPARα/RXRα nuclear receptors, comprising PGC-1α and FOXO1, two key regulators critically involved not only in the metabolic functions of the liver but also in the life cycle of HBV, acting as essential transcription factors for viral gene expression. These findings were confirmed by gene expression of microdissected hepatocytes. Moreover, LCM of malignant hepatocytes also revealed up-regulation of unique genes associated with cancer and signaling Pathways, including two novel HCC-associated cancer testis antigen genes, NUF2 and TTK. Conclusions: Integrated gene expression profiling of whole liver tissue with that of microdissected hepatocytes demonstrated that HBV-associated HCC is characterized by a metabolism switch-off and by a significant reduction in HBsAg. LCM proved to be a critical tool to validate gene signatures associated with HCC and to identify genes that may play a role in hepatocarcinogenesis, opening new perspectives for the discovery of novel diagnostic markers and therapeutic targets

Evaluating Differential Gene Expression Using RNA-Sequencing: A Case Study in Diet-Induced Mouse Model Associated with Non-Alcoholic Fatty Liver Disease (NAFLD) and CXCL12-Vs- TGFβ Induced Fibroblast to Myofibroblast Phenoconversion

Unlike the genome, cell transcriptome is dynamic and specific for a given cell developmental stage. Transcriptomics study is crucial to understand the functional elements of the genome to divulge molecular constituents of cells. The recent development of high-throughput sequencing technologies has provided an unprecedented method to sequence RNA and it has been emerging as the preferred technology for both characterization and quantification of the cell transcripts. Using “Tailor_Pipeline” we have analyzed diet-induced mouse and stromal fibroblast RNA-Seq samples and deciphers the differentially expressed genes that were significantly up- and downregulated and associated with several metabolic immune responses that presumably associated with liver disease. Analyzing the diet-induced mice model allowed us to encapsulate the transcriptional differences between diet-induced mice that can aid in the understanding of NAFLD and consequent liver pathogenesis. Identification of genes downregulated in metabolic processes and upregulated in immune responses indicate that mice model exhibiting liver disease. Moreover, the finding of a premalignant signature suggests that NAFLD may begin to progress towards hepatocellular carcinoma much earlier than earlier consideration. Tissue fibrosis arises due to overgrowth, scarring of various tissues and is attributed to deposition of the extracellular matrix including collagen, influenced by the actions of several pro-fibrotic proteins that can induce myofibroblast phenoconversion. Though recent transcriptomics analysis reveals the cellular identity, its ability to provide biologically meaningful insights in fibrosis is largely unexplored. To unravel the mechanisms at the genetic level, we have considered TGFβ/TGFβR and CXCL12/CXCR4 transcriptomes in human stromal fibroblasts. Transcriptome profiling technology revealed CXCL12/CXCR4 axis is responsible for the activation of COPII vesicle formation, ubiquitination, and Golgi/ER localization/targeting. Especially, identification of CUL3 and KLHL12 are responsible for the transportation of procollagen from ER to the Golgi. Interestingly, over-expression of CUL3 and KLHL12 are highly correlated with procollagen secretion by CXCL12-treated cells, but not in TGFβ-, treated cells. Moreover, this analysis showed how activation of the CXCL12/CXCR4 axis promotes procollagen I secretion that responsible for the deposition of ECM which is a characteristic of fibrosis

Systems analysis of host-parasite interactions.

Parasitic diseases caused by protozoan pathogens lead to hundreds of thousands of deaths per year in addition to substantial suffering and socioeconomic decline for millions of people worldwide. The lack of effective vaccines coupled with the widespread emergence of drug-resistant parasites necessitates that the research community take an active role in understanding host-parasite infection biology in order to develop improved therapeutics. Recent advances in next-generation sequencing and the rapid development of publicly accessible genomic databases for many human pathogens have facilitated the application of systems biology to the study of host-parasite interactions. Over the past decade, these technologies have led to the discovery of many important biological processes governing parasitic disease. The integration and interpretation of high-throughput -omic data will undoubtedly generate extraordinary insight into host-parasite interaction networks essential to navigate the intricacies of these complex systems. As systems analysis continues to build the foundation for our understanding of host-parasite biology, this will provide the framework necessary to drive drug discovery research forward and accelerate the development of new antiparasitic therapies