PATIENTS AND METHODS: We report two siblings of a healthy but consanguineous Malaysian family presenting with severe short stature caused by CPHD with a variable phenotype. Importantly, at the beginning the girl presented with isolated GHD, whereas the boy was hypothyroid. As the most common gene alterations responsible for CPHD are within either the PROP-1- or the POU1F1- (PIT-1)-gene these two genes were further studied.
RESULTS: Subsequent sequencing of the six exons of the POU1F1-gene allowed the identification of a new N-terminal mutation (Q4ter) in these two children. A substitution of C to T induced a change from a glutamine (CAA) to a stop codon (TAA) in exon 1 of the PIT-1 protein. Both affected children were homozygous for the mutation, whereas the mother and father were heterozygous.
CONCLUSION: We describe two children with autosomal recessive inherited CPHD caused by a new N-terminal located mutation within the PUO1F1-gene. The clinical history of these two children underline the phenotypic variability and support the fact that children with any isolated and/or combined PHD need to be closely followed as at an any time other hormonal deficiencies may occur. In addition, molecular analysis of the possible genes involved might be most helpful for the future follow-up.
OBJECTIVE: We previously identified AtWRKY50 as a transcriptional activator of SAR gene PR1. Although PR1 accumulates to high levels in plants after attack by pathogens, its function is still elusive. Here we investigated the effects of overexpression of several WRKY proteins, including AtWRKY50, on the metabolome of Arabidopsis thaliana.
METHODS: The influence of overexpression of WRKY proteins on the metabolites of Arabidopsis was investigated by using an NMR spectroscopy-based metabolomic approach. The 1H NMR data was analysed using the multivariate data analysis methods, such as principal component analysis, hierarchical cluster analysis and partial least square-discriminant analysis.
RESULTS: The results showed that the metabolome of transgenic Arabidopsis seedlings overexpressing AtWRKY50 was different from wild type Arabidopsis and transgenic Arabidopsis overexpressing other WRKY genes. Amongst other metabolites, sinapic acid and 1-O-sinapoyl-β-D-glucose especially appeared to be the most prominent discriminating metabolites, accumulating to levels 2 to 3 times higher in the AtWRKY50 overexpressor lines.
CONCLUSION: Our results indicate a possible involvement of AtWRKY50 in secondary metabolite production in Arabidopsis, in particular of hydroxycinnamates such as sinapic acid and 1-O-sinapoyl-β-D-glucose.
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.
RESULTS: A total of 3412 (2001 annotated) gene candidates were found to be significantly differentially expressed between high- and low-yielding palms at at least one of the different stages of mesocarp development evaluated. Gene Ontologies (GO) enrichment analysis identified 28 significantly enriched GO terms, including regulation of transcription, fatty acid biosynthesis and metabolic processes. These differentially expressed genes comprise several transcription factors, such as, bHLH, Dof zinc finger proteins and MADS box proteins. Several genes involved in glycolysis, TCA, and fatty acid biosynthesis pathways were also found up-regulated in high-yielding oil palm, among them; pyruvate dehydrogenase E1 component Subunit Beta (PDH), ATP-citrate lyase, β- ketoacyl-ACP synthases I (KAS I), β- ketoacyl-ACP synthases III (KAS III) and ketoacyl-ACP reductase (KAR). Sucrose metabolism-related genes such as Invertase, Sucrose Synthase 2 and Sucrose Phosphatase 2 were found to be down-regulated in high-yielding oil palms, compared to the lower yield palms.
CONCLUSIONS: Our findings indicate that a higher carbon flux (channeled through down-regulation of the Sucrose Synthase 2 pathway) was being utilized by up-regulated genes involved in glycolysis, TCA and fatty acid biosynthesis leading to enhanced oil production in the high-yielding oil palm. These findings are an important stepping stone to understand the processes that lead to production of high-yielding oil palms and have implications for breeding to maximize oil production.