Global risk transformative prioritization for prostate cancer candidate genes in molecular networks

Understanding the pathogenesis of complex diseases is aided by precise identification of the genes responsible. Many computational methods have been developed to prioritize candidate disease genes, but coverage of functional annotations may be a limiting factor for most of these methods. Here, we introduce a global candidate gene prioritization approach that considers information about network properties in the human protein interaction network and risk transformative contents from known disease genes. Global risk transformative scores were then used to prioritize candidate genes. This method was introduced to prioritize candidate genes for prostate cancer. The effectiveness of our global risk transformative algorithm for prioritizing candidate genes was evaluated according to validation studies. Compared with ToppGene and random walk-based methods, our method outperformed the two other candidate gene prioritization methods. The generality of our method was assessed by testing it on prostate cancer and other types of cancer. The performance was evaluated using standard leave-one-out cross-validation.     

PICALM rs3851179 Variant Confers Susceptibility to Alzheimer’s Disease in Chinese Population

The association between PICALM rs3851179 variant and Alzheimer’s disease (AD) has been well established by previous genome-wide association studies (GWAS) and candidate gene studies in European population. Recent studies investigated the association between PICALM rs3851179 and AD susceptibility in Chinese population. However, these studies reported consistent and inconsistent results. Here, we selected 9435 samples including 3704 AD cases and 5731 controls from previous studies and evaluated this association using a meta-analysis method for additive model. We did not observe significant genetic heterogeneity in Chinese population. Our results indicate significant association between PICALM rs3851179 and AD in Chinese population. The sensitivity analysis indicates that the association between rs3851179 and AD did not vary substantially. The regression analysis suggests no significant publication bias. In summary, this updated meta-analysis highlights the involvement of PICALM rs3851179 variant in Alzheimer’s disease susceptibility in Chinese population.     

Expression profiling and integrative analysis of the <Emphasis Type="Italic">CESA</Emphasis>/<Emphasis Type="Italic">CSL</Emphasis> superfamily in rice

Background  

The cellulose synthase and cellulose synthase-like gene superfamily (CESA/CSL) is proposed to encode enzymes for cellulose and non-cellulosic matrix polysaccharide synthesis in plants. Although the rice (Oryza sativa L.) genome has been sequenced for a few years, the global expression profiling patterns and functions of the OsCESA/CSL superfamily remain largely unknown.     

Global Identification of Multiple OsGH9 Family Members and Their Involvement in Cellulose Crystallinity Modification in Rice

Plant glycoside hydrolase family 9 (GH9) comprises typical endo-β-1,4-glucanase (EGases, EC3.2.1.4). Although GH9A (KORRIGAN) family genes have been reported to be involved in cellulose biosynthesis in plants, much remains unknown about other GH9 subclasses. In this study, we observed a global gene co-expression profiling and conducted a correlation analysis between OsGH9 and OsCESA among 66 tissues covering most periods of life cycles in 2 rice varieties. Our results showed that OsGH9A3 and B5 possessed an extremely high co-expression with OsCESA1, 3, and 8 typical for cellulose biosynthesis in rice. Using two distinct rice non-GH9 mutants and wild type, we performed integrative analysis of gene expression level by qRT-PCR, cellulase activities in situ and in vitro, and lignocellulose crystallinity index (CrI) in four internodes of stem tissues. For the first time, OsGH9B1, 3, and 16 were characterized with the potential role in lignocellulose crystallinity alteration in rice, whereas OsGH9A3 and B5 were suggested for cellulose biosynthesis. In addition, phylogenetic analysis and gene co-expression comparison revealed GH9 function similarity in Arabidopsis and rice. Hence, the data can provide insights into GH9 function in plants and offer the potential strategy for genetic manipulation of plant cell wall using the five aforementioned novel OsGH9 genes.     

Prioritizing genes responsible for host resistance to influenza using network approaches

Background

The genetic make-up of humans and other mammals (such as mice) affects their resistance to influenza virus infection. Considering the complexity and moral issues associated with experiments on human subjects, we have only acquired partial knowledge regarding the underlying molecular mechanisms. Although influenza resistance in inbred mice has been mapped to several quantitative trait loci (QTLs), which have greatly narrowed down the search for host resistance genes, only few underlying genes have been identified.

Results

To prioritize a list of promising candidates for future functional investigation, we applied network-based approaches to leverage the information of known resistance genes and the expression profiles contrasting susceptible and resistant mouse strains. The significance of top-ranked genes was supported by different lines of evidence from independent genetic associations, QTL studies, RNA interference (RNAi) screenings, and gene expression analysis. Further data mining on the prioritized genes revealed the functions of two pathways mediated by tumor necrosis factor (TNF): apoptosis and TNF receptor-2 signaling pathways. We suggested that the delicate balance between TNF’s pro-survival and apoptotic effects may affect hosts’ conditions after influenza virus infection.

Conclusions

This study considerably cuts down the list of candidate genes responsible for host resistance to influenza and proposed novel pathways and mechanisms. Our study also demonstrated the efficacy of network-based methods in prioritizing genes for complex traits.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-14-816) contains supplementary material, which is available to authorized users.     

Analyzing Large-Scale Samples Confirms the Association Between the ABCA7 rs3764650 Polymorphism and Alzheimer’s Disease Susceptibility

Large-scale genome-wide association studies (GWAS) have revealed that the ABCA7 rs3764650 polymorphism (or its proxies, namely rs115550680, rs3752246, and rs4147929) is associated with Alzheimer’s disease (AD) susceptibility in individuals of Caucasian ancestry. The following studies have investigated this finding in Chinese (N?=?633 and N?=?1,224), Japanese (N?=?1,735), Korean (N?=?844), African American (N?=?5,896), and Canadian (N?=?1,104) populations. However, these studies reported a weak or negligible association. We hypothesized that these negative results may have been caused by either relatively small sample sizes compared with those used for the previous GWAS in individuals of Caucasian ancestry or the genetic heterogeneity of the rs3764650 polymorphism (or its proxies) in different populations. Here, we reevaluated the association between rs3764650 and AD using large-scale samples from 18 previous studies (N?=?79,381—30,590 cases and 48,791 controls) by searching PubMed, AlzGene, and Google Scholar databases. Using allele, dominant, recessive, and additive models, we did not identify significant heterogeneity among the 18 studies. We observed a significant association between rs3764650 and AD using the allele (P?=?1.76E???26, odds ratio (OR)?=?1.21, 95 % confidence interval (CI) 1.17–1.26), dominant (P?=?4.00E???04, OR?=?1.17, 95 % CI 1.07–1.28), recessive (P?=?3.00E???03, OR?=?1.43, 95 % CI 1.13–1.81), and additive models (P?=?3.00E???03, OR?=?1.49, 95 % CI 1.16–1.91). Collectively, our analysis further supports previous findings that the ABCA7 rs3764650 polymorphism is associated with AD susceptibility. We believe that our findings will be very useful for future genetic studies on AD.