Detecting pathway relationship in the context of human protein-protein interaction network and its application to Parkinson's disease.

In human physiological conditions like complex diseases, a large number of genes/proteins, as well as their interactions, are involved. Thus, detecting the biochemical pathways enriched in these genes/proteins and identifying the pathway relationships is critical to understand the molecular mechanisms underlying a disease and can also be valuable in selecting the potential molecular targets for further exploration. In this study, we proposed a method to measure the relationship between pathways based on their distribution in the human PPI network. By representing each pathway as a gene module in the PPI network, a distance was calculated to measure the closeness of two pathways. For the pathways in the KEGG database, a total of 2143 pathway pairs with close connections were identified. Additional evaluations indicated the pathway relationship built via such approach was consistent with available evidence. Further, based on the genes and pathways potentially associated with the pathogenesis of Parkinson's disease (PD), we analyzed the pathway relationship and identified the major pathways related to this disorder via the new method. Also, by analyzing the pathway interaction network constructed by the identified major pathways, we explored the potential pathway targets that may be important in the etiology and development of PD. In summary, we proposed an approach to measure the relationship between pathways, which could provide a more systematic profile on pathways involved in a phenotype, and may also help to improve the result of pathway enrichment analysis.

Characterization of the complete chloroplast genome of Hevea pauciflora (Euphorbiaceae), an important wild relative of the rubber tree.

Hevea pauciflora belongs to the Euphorbiaceae family, an important wild relative of the rubber tree. This study sequenced, assembled, and annotated the complete chloroplast genome of H. pauciflora. The complete chloroplast genome is 161,123 bp with a canonical quadripartite structure containing a large single-copy (LSC) region (89,109 bp), a small single-copy (SSC) region (18,376 bp), and two inverted repeat regions (IRa and IRb) (26,819 bp, each). A total of 134 genes were annotated, including 86 protein-coding genes, four pseudogenes, 36 tRNA genes, and eight rRNA genes. The 134 genes include four major groups: 'self-replication', 'photosynthesis', 'unknown function', and 'others'. A phylogenetic analysis clustered H. pauciflora, H. brasiliensis, H. camargoana, and H. benthamiana into one clade, consistent with traditional taxonomy. This study provides useful data for further studies of Hevea genus and the phylogenetic relationships of Euphorbiaceae species.

The complete chloroplast genome of Hevea camargoana.

Hevea camargoana is a natural latex producing tropical plant and a close relative of H. brasiliensis, the primary commercial source of natural rubber. This study sequenced and analyzed the chloroplast genome of H. camargoana. The circular chloroplast genome of H. camargoana contains 161,291 bp with a GC content of 35.72%. This region contains two inverted repeat regions (26,819 bp), a large single-copy region (89,281 bp), and a small single-copy (18,372 bp) region in the complete chloroplast genome. A total of 134 genes were annotated, including 86 protein-coding genes, 36 transfer RNA genes, 8 ribosomal RNA genes, and 4 pseudogenes. The results showed that H. camargoana and H. brasiliensis were closely related, suggesting that H. camargoana may be used for the future variety improvement of rubber trees.

Complete chloroplast genome of Hevea benthamiana, a SALB-resistant relative wild species of rubber tree.

Hevea benthamiana is a SALB-resistant wild species of H. brasiliensis, the only source of mass production of high quality natural rubber. This study sequenced and analyzed the chloroplast genome of H. benthamiana. The chloroplast genome of H. benthamiana contains 161,124 bp and consists of 51,495 bp of A (31.96%), 52,022 bp of T (32.29%), 28,915 bp of G (17.95%), and 28,692 bp of C (17.81%). The ring-shaped genome includes four regions: a large single-copy region (LSC, 89,110 bp), a small single copy (SSC, 18,376 bp) region, and two inverted repeat regions (IRs, 26,819 bp). A total of 134 genes were annotated, of which 86 encode proteins; four are pseudogenes; 36 are tRNA genes, and eight are rRNA genes. Phylogenetic analyses showed that H. benthamiana is very closely related to H. Brasiliensis, this result indicates that H. benthamiana is highly valuable for the breeding of SALB-resistant varieties of rubber trees.

Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach.

BACKGROUND: Our understanding of the molecular mechanisms underlying Alzheimer's disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease. METHOD: In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm. RESULTS: We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules-neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module-indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified. CONCLUSION: By means of network and pathway-based methodology, we explored the pathogenetic mechanism underlying AD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular mechanism underlying AD. In addition, the framework proposed in this study could be used to investigate the pathological molecular network and genes relevant to other complex diseases or phenotypes.