Programmed cell death and new discoveries in the genetics of parkinsonism

The concept that activation of cellular pathways of programmed cell death (PCD) may lead to the death of neurons has been an important hypothesis for adult neurodegenerative diseases. For Parkinson's disease (PD), up until now, the evidence for this hypothesis has largely been of two types: clear evidence of a role for PCD in neurotoxin models of the disease, and somewhat controversial evidence from human postmortem studies. With the rapid pace of discoveries in recent years of the genetic basis of PD, a new form of evidence has emerged. The prevailing concept of the role for PCD in PD has been that its mediators are 'downstream' effectors of more proximate and specific causes related to genetic or environmental factors. However, recent studies of three genes which cause autosomal recessive forms of parkinsonism, parkin, PTEN-induced kinase, and DJ-1, suggest that they may have more intimate relationships with the mediators of PCD and that loss-of-function mutations may result in an increased propensity for neurons to die. Intriguingly, independent studies of the function of these genes have suggested that they may share roles in regulating survival signaling pathways, such as those mediated by the survival signaling kinase Akt. Further elucidation of these relationships will have implications for the pathogenesis and neuroprotective treatment of PD.     

拟南芥转录因子GRAS 家族基因群响应渗透和干旱胁迫的初步探索

GRAS家族是一类植物特有的转录调控因子, 已有报道表明该家族基因在植物生长发育和光信号转导过程中具有重要作用。目前在拟南芥(Arabidopsis thaliana)基因组中已鉴定了33个GRAS家族基因。利用功能基因组学和生物信息学手段,通过基因芯片数据挖掘和基因功能预测, 对拟南芥GRAS家族基因在渗透和干旱胁迫过程中的应答模式进行了初步探索, 提出了一类响应渗透胁迫和干旱胁迫的拟南芥GRAS家族基因。以SCL13为例, 利用基因芯片相关性和GO分析, 对其在渗透胁迫信号转导过程中可能的调控机制进行了预测和分析。这一研究将为阐明GRAS家族基因参与水分胁迫的分子机制提供新的思路, 同时也为植物抗逆分子育种提供候选基因。     

Characterization of Chemically Induced Liver Injuries Using Gene Co-Expression Modules

Liver injuries due to ingestion or exposure to chemicals and industrial toxicants pose a serious health risk that may be hard to assess due to a lack of non-invasive diagnostic tests. Mapping chemical injuries to organ-specific damage and clinical outcomes via biomarkers or biomarker panels will provide the foundation for highly specific and robust diagnostic tests. Here, we have used DrugMatrix, a toxicogenomics database containing organ-specific gene expression data matched to dose-dependent chemical exposures and adverse clinical pathology assessments in Sprague Dawley rats, to identify groups of co-expressed genes (modules) specific to injury endpoints in the liver. We identified 78 such gene co-expression modules associated with 25 diverse injury endpoints categorized from clinical pathology, organ weight changes, and histopathology. Using gene expression data associated with an injury condition, we showed that these modules exhibited different patterns of activation characteristic of each injury. We further showed that specific module genes mapped to 1) known biochemical pathways associated with liver injuries and 2) clinically used diagnostic tests for liver fibrosis. As such, the gene modules have characteristics of both generalized and specific toxic response pathways. Using these results, we proposed three gene signature sets characteristic of liver fibrosis, steatosis, and general liver injury based on genes from the co-expression modules. Out of all 92 identified genes, 18 (20%) genes have well-documented relationships with liver disease, whereas the rest are novel and have not previously been associated with liver disease. In conclusion, identifying gene co-expression modules associated with chemically induced liver injuries aids in generating testable hypotheses and has the potential to identify putative biomarkers of adverse health effects.     

An Effective Method to Identify Shared Pathways and Common Factors among Neurodegenerative Diseases

Groups of distinct but related diseases often share common symptoms, which suggest likely overlaps in underlying pathogenic mechanisms. Identifying the shared pathways and common factors among those disorders can be expected to deepen our understanding for them and help designing new treatment strategies effected on those diseases. Neurodegeneration diseases, including Alzheimer''s disease (AD), Parkinson''s disease (PD) and Huntington''s disease (HD), were taken as a case study in this research. Reported susceptibility genes for AD, PD and HD were collected and human protein-protein interaction network (hPPIN) was used to identify biological pathways related to neurodegeneration. 81 KEGG pathways were found to be correlated with neurodegenerative disorders. 36 out of the 81 are human disease pathways, and the remaining ones are involved in miscellaneous human functional pathways. Cancers and infectious diseases are two major subclasses within the disease group. Apoptosis is one of the most significant functional pathways. Most of those pathways found here are actually consistent with prior knowledge of neurodegenerative diseases except two cell communication pathways: adherens and tight junctions. Gene expression analysis showed a high probability that the two pathways were related to neurodegenerative diseases. A combination of common susceptibility genes and hPPIN is an effective method to study shared pathways involved in a group of closely related disorders. Common modules, which might play a bridging role in linking neurodegenerative disorders and the enriched pathways, were identified by clustering analysis. The identified shared pathways and common modules can be expected to yield clues for effective target discovery efforts on neurodegeneration.     

Deciphering Ascorbic Acid Regulatory Pathways in Ripening Tomato Fruit Using a Weighted Gene Correlation Network Analysis Approach

Genotype is generally determined by the co-expression of diverse genes and multiple regulatory pathways in plants. Gene co-expression analysis combining with physiological trait data provides very important information about the gene function and regulatory mechanism. L-Ascorbic acid （AsA）, which is an essential nutrient component for human health and plant metabolism, plays key roles in diverse biological processes such as cell cycle, cell expansion, stress resistance, hormone synthesis, and signaling. Here, we applied a weighted gene correlation network analysis approach based on gene expression values and AsA content data in ripening tomato （Solanum lycopersicum L.） fruit with different AsA content levels, which leads to identification of AsA relevant modules and vital genes in AsA regulatory pathways. Twenty- four modules were compartmentalized according to gene expression profiling. Among these modules, one negatively related module containing genes involved in redox processes and one positively related module enriched with genes involved in AsA biosynthetic and recycling pathways were further analyzed. The present work herein indicates that redox pathways as well as hormone-signal pathways are closely correlated with AsA accumulation in ripening tomato fruit, and allowed us to prioritize candidate genes for follow-up studies to dissect this interplay at the biochemical and molecular level.     

Analysis of gene co-expression networks and function modules at different developmental stages of chicken breast muscle

The development of poultry muscle fibers after hatching is closely related to meat quality and production efficiency. It is necessary to identify functional modules (groups of functionally related genes) related to muscle development at different developmental stages, and to investigate their relationships based on the weighted gene co-expression network analysis (WGCNA) methods. Accordingly, we investigated the co-expression associations between genes related to chicken breast muscle at four different developmental stages (between 2 and 14 weeks of age), and systematically analyzed the network topology in Jinmao Hua chicken. As a result, 2341 differentially expressed genes were identified and subjected to co-expression analysis. Four modules were identified to be related to a particular growth stage for the development of breast muscle. A series of genes with the highest connectivity were identified in the pink (2 weeks), yellow (6 weeks), green (10 weeks) and black modules (14 weeks), respectively, and visualized by Cytoscape. These hub genes (FGF, MAPKAPK5, NRG1, SCD, ACSL1, PPAR etc.) were mainly enriched in 15 pathways, such as MAPK signaling pathway, NRG/ErbB signaling pathway, and insulin signaling pathway. They shared biological functions related to development of breast muscle and adipogenesis. This is the first study of gene network with different stages of muscle development in Jinmao Hua chicken to observe co-expression patterns. It may contribute to the underlied molecular mechanisms of chicken breast muscle development.