Network-based Analysis of Genome Wide Association Data Provides Novel Candidate Genes for Lipid and Lipoprotein Traits

Genome wide association studies (GWAS) identify susceptibility loci for complex traits, but do not identify particular genes of interest. Integration of functional and network information may help in overcoming this limitation and identifying new susceptibility loci. Using GWAS and comorbidity data, we present a network-based approach to predict candidate genes for lipid and lipoprotein traits. We apply a prediction pipeline incorporating interactome, co-expression, and comorbidity data to Global Lipids Genetics Consortium (GLGC) GWAS for four traits of interest, identifying phenotypically coherent modules. These modules provide insights regarding gene involvement in complex phenotypes with multiple susceptibility alleles and low effect sizes. To experimentally test our predictions, we selected four candidate genes and genotyped representative SNPs in the Malmö Diet and Cancer Cardiovascular Cohort. We found significant associations with LDL-C and total-cholesterol levels for a synonymous SNP (rs234706) in the cystathionine beta-synthase (CBS) gene (p = 1 × 10⁻⁵ and adjusted-p = 0.013, respectively). Further, liver samples taken from 206 patients revealed that patients with the minor allele of rs234706 had significant dysregulation of CBS (p = 0.04). Despite the known biological role of CBS in lipid metabolism, SNPs within the locus have not yet been identified in GWAS of lipoprotein traits. Thus, the GWAS-based Comorbidity Module (GCM) approach identifies candidate genes missed by GWAS studies, serving as a broadly applicable tool for the investigation of other complex disease phenotypes.Genome wide association studies (GWAS)¹ meta-analyses have pinpointed a number of new gene regions contributing to multifactorial diseases. GWAS typically find limited numbers of loci that contribute modestly to complex phenotypes (1), and GLGC meta-analysis of GWAS data has reached the limit of what can be expected (2) without the use of alternative strategies. Given that susceptibility loci for complex traits are unlikely to be randomly distributed in the genome (3), we might expect that the genes associated with a disease will be more likely to be present within the same pathways or functional groupings. In published cases, pathway based GWAS analysis provides an alternative approach to the dissection of complex disease traits (4, 5). In addition, nominal GWAS p values superimposed upon the human molecular network have been used to identify genes associated with multiple sclerosis (6), and the disease association protein–protein link evaluator (DAPPLE) has been used to find significant interactions among proteins encoded by genes in loci associated with other particular diseases (7). Other approaches incorporate heterogeneous molecular data such as linkage studies, cross species conservation measures, gene expression data and protein–protein interactions to better understand GWAS results (8, 9). Integrating molecular network information, pathway analyses, and GWAS data thus holds promise for identifying new susceptibility loci and improving the identification of relevant candidate genes.If a gene is involved in a specific functional process or disease, its molecular network neighbors might also be suspected to have some role (3). In line with this “local” hypothesis, proteins involved in the same disease show a high propensity to interact (10) or cluster together (11) with each other. Interactions between variations in multiple genes, each with strong or modest effects, perturbing the same pathways or modules, may govern complex traits (3, 6). The molecular triangulation (MT) algorithm can be applied to rank seed genes according to their common disease associated neighbors, assigning closer and more connected neighbors higher values (12). Interactions between modestly associated MT genes may be indicative of coherent disease pathways or of genes conferring susceptibility to disease in a coordinated manner. The jActiveModule method (13) combines seed gene scores with biologically relevant interactions to identify network modules where perturbations causative of disease are more likely to reside. Lastly, although not yet implemented at the module level, phenotypic coherence between interacting pairs of genes has been quantified using the combination of molecular level gene to disease relationships and Medicare comorbidity data (14, 15).We believe that GWAS significant SNPs and variants representing potential candidate genes can use the above strategies to reveal more about the missing heritability of complex phenotypes. The most important risk factors for coronary artery disease (CAD) include serum concentrations of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG). We present a GWAS-based meta-analysis Comorbid Module (GCM) approach that uses significant (p < 5 × 10⁻⁸) GWAS signals for these four traits in the context of molecular networks to prioritize modules of disease-associated candidate genes. We evaluate our approach experimentally through allelic association and genotyping within the Malmö Diet and Cancer Cardiovascular Cohort (MDC-CC) for SNPs representing top candidate genes.     

Characterization of Cyanobacterial Hydrocarbon Composition and Distribution of Biosynthetic Pathways

Cyanobacteria possess the unique capacity to naturally produce hydrocarbons from fatty acids. Hydrocarbon compositions of thirty-two strains of cyanobacteria were characterized to reveal novel structural features and insights into hydrocarbon biosynthesis in cyanobacteria. This investigation revealed new double bond (2- and 3-heptadecene) and methyl group positions (3-, 4- and 5-methylheptadecane) for a variety of strains. Additionally, results from this study and literature reports indicate that hydrocarbon production is a universal phenomenon in cyanobacteria. All cyanobacteria possess the capacity to produce hydrocarbons from fatty acids yet not all accomplish this through the same metabolic pathway. One pathway comprises a two-step conversion of fatty acids first to fatty aldehydes and then alkanes that involves a fatty acyl ACP reductase (FAAR) and aldehyde deformylating oxygenase (ADO). The second involves a polyketide synthase (PKS) pathway that first elongates the acyl chain followed by decarboxylation to produce a terminal alkene (olefin synthase, OLS). Sixty-one strains possessing the FAAR/ADO pathway and twelve strains possessing the OLS pathway were newly identified through bioinformatic analyses. Strains possessing the OLS pathway formed a cohesive phylogenetic clade with the exception of three Moorea strains and Leptolyngbya sp. PCC 6406 which may have acquired the OLS pathway via horizontal gene transfer. Hydrocarbon pathways were identified in one-hundred-forty-two strains of cyanobacteria over a broad phylogenetic range and there were no instances where both the FAAR/ADO and the OLS pathways were found together in the same genome, suggesting an unknown selective pressure maintains one or the other pathway, but not both.     

SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing

The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.     

AtMND1 is required for homologous pairing during meiosis in Arabidopsis

Background  

Pairing of homologous chromosomes at meiosis is an important requirement for recombination and balanced chromosome segregation among the products of meiotic division. Recombination is initiated by double strand breaks (DSBs) made by Spo11 followed by interaction of DSB sites with a homologous chromosome. This interaction requires the strand exchange proteins Rad51 and Dmc1 that bind to single stranded regions created by resection of ends at the site of DSBs and promote interactions with uncut DNA on the homologous partner. Recombination is also considered to be dependent on factors that stabilize interactions between homologous chromosomes. In budding yeast Hop2 and Mnd1 act as a complex to promote homologous pairing and recombination in conjunction with Rad51 and Dmc1.     

Interrelations of mitochondrial fragmentation and cell death under ischemia/reoxygenation and UV-irradiation: protective effects of SkQ1, lithium ions and insulin

Mitochondria-targeted antioxidant 10-(6-plastoquinonyl)decyltriphenyl-phosphonium (SkQ1) as well as insulin and the inhibitor of glycogen-synthase kinase, Li(+) are shown to (i) protect renal tubular cells from an apoptotic death and (ii) diminish mitochondrial fission (the thread-grain transition) induced by ischemia/reoxygenation. However, SkQ1 and LiCl protected the mitochondrial reticulum of skin fibroblasts from ultraviolet-induced fission but were ineffective in preventing a further cell death. This means that mitochondrial fission is not essential for apoptotic cascade progression.     

Myoglobin causes oxidative stress,increase of NO production and dysfunction of kidney's mitochondria

Rhabdomyolysis or crush syndrome is a pathology caused by muscle injury resulting in acute renal failure. The latest data give strong evidence that this syndrome caused by accumulation of muscle breakdown products in the blood stream is associated with oxidative stress with primary role of mitochondria. In order to evaluate the significance of oxidative stress under rhabdomyolysis we explored the direct effect of myoglobin on renal tubules and isolated kidney mitochondria while measuring mitochondrial respiratory control, production of reactive oxygen and nitrogen species and lipid peroxidation. In parallel, we evaluated mitochondrial damage under myoglobinurea in vivo. An increase of lipid peroxidation products in kidney mitochondria and release of cytochrome c was detected on the first day of myoglobinuria. In mitochondria incubated with myoglobin we detected respiratory control drop, uncoupling of oxidative phosphorylation, an increase of lipid peroxidation products and stimulated NO synthesis. Mitochondrial pore inhibitor, cyclosporine A, mitochondria-targeted antioxidant (SkQ1) and deferoxamine (Fe-chelator and ferryl-myoglobin reducer) abrogated these events. Similar effects (oxidative stress and mitochondrial dysfunction) were revealed when myoglobin was added to isolated renal tubules. Thus, rhabdomyolysis can be considered as oxidative stress-mediated pathology with mitochondria to be the primary target and possibly the source of reactive oxygen and nitrogen species. We speculate that rhabdomyolysis-induced kidney damage involves direct interaction of myoglobin with mitochondria possibly resulting in iron ions release from myoglobin's heme, which promotes the peroxidation of mitochondrial membranes. Usage of mitochondrial permeability transition blockers, Fe-chelators or mitochondria-targeted antioxidants, may bring salvage from this pathology.