Stratification of candidate genes for Parkinson’s disease using weighted protein interaction network analysis

Genome wide association studies (GWAS) have helped identify large numbers of genetic loci that significantly associate with increased risk of developing diseases. However, translating genetic knowledge into understanding of the molecular mechanisms underpinning disease (i.e. disease-specific impacted biological processes) has to date proved to be a major challenge. This is primarily due to difficulties in confidently defining candidate genes at GWAS-risk loci. The goal of this study was to better characterize candidate genes within GWAS loci using a protein interactome based approach and with Parkinson's disease (PD) data as a test case.We applied a recently developed Weighted Protein-Protein Interaction Network Analysis (WPPINA) pipeline as a means to define impacted biological processes, risk pathways and therein key functional players. We used previously established Mendelian forms of PD to identify seed proteins, and to construct a protein network for genetic Parkinson's and carried out functional enrichment analyses. We isolated PD-specific processes indicating 'mitochondria stressors mediated cell death', 'immune response and signaling', and 'waste disposal' mediated through 'autophagy'. Merging the resulting protein network with data from Parkinson's GWAS we confirmed 10 candidate genes previously selected by pure proximity and were able to nominate 17 novel candidate genes for sporadic PD.With this study, we were able to better characterize the underlying genetic and functional architecture of idiopathic PD, thus validating WPPINA as a robust pipeline for the in silico genetic and functional dissection of complex disorders

BMC Genomics

BackgroundIncreased reports of Neisseria meningitidis urethritis in multiple U.S. cities during 2015 have been attributed to the emergence of a novel clade of nongroupable N. meningitidis within the ST-11 clonal complex, the \u201cU.S. NmNG urethritis clade\u201d. Genetic recombination with N. gonorrhoeae has been proposed to enable efficient sexual transmission by this clade. To understand the evolutionary origin and diversification of the U.S. NmNG urethritis clade, whole-genome phylogenetic analysis was performed to identify its members among the N. meningitidis strain collection from the Centers for Disease Control and Prevention, including 209 urogenital and rectal N. meningitidis isolates submitted by U.S. public health departments in eleven states starting in 2015.ResultsThe earliest representatives of the U.S. NmNG urethritis clade were identified from cases of invasive disease that occurred in 2013. Among 209 urogenital and rectal isolates submitted from January 2015 to September 2016, the clade accounted for 189/198 male urogenital isolates, 3/4 female urogenital isolates, and 1/7 rectal isolates. In total, members of the clade were isolated in thirteen states between 2013 and 2016, which evolved from a common ancestor that likely existed during 2011. The ancestor contained N. gonorrhoeae-like alleles in three regions of its genome, two of which may facilitate nitrite-dependent anaerobic growth during colonization of urogenital sites. Additional gonococcal-like alleles were acquired as the clade diversified. Notably, one isolate contained a sequence associated with azithromycin resistance in N. gonorrhoeae, but no other gonococcal antimicrobial resistance determinants were detected.ConclusionsInterspecies genetic recombination contributed to the early evolution and subsequent diversification of the U.S. NmNG urethritis clade. Ongoing acquisition of N. gonorrhoeae alleles by the U.S. NmNG urethritis clade may facilitate the expansion of its ecological niche while also increasing the frequency with which it causes urethritis.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4560-x) contains supplementary material, which is available to authorized users.2018-03-02T00:00:00Z29499642PMC583483

BMC Genomics

BackgroundDietary intakes of red meat and fat are established risk factors for both colorectal cancer (CRC) and cardiovascular disease (CVDs). Recent studies have shown a mechanistic link between TMAO, an intestinal microbial metabolite of red meat and fat, and risk of CVDs. Data linking TMAO directly to CRC is, however, lacking. Here, we present an unbiased data-driven network-based systems approach to uncover a potential genetic relationship between TMAO and CRC.Materials and methodsWe constructed two different epigenetic interaction networks (EINs) using chemical-gene, disease-gene and protein-protein interaction data from multiple large-scale data resources. We developed a network-based ranking algorithm to ascertain TMAO-related diseases from EINs. We systematically analyzed disease categories among TMAO-related diseases at different ranking cutoffs. We then determined which genetic pathways were associated with both TMAO and CRC.ResultsWe show that CVDs and their major risk factors were ranked highly among TMAO-related diseases, confirming the newly discovered mechanistic link between CVDs and TMAO, and thus validating our algorithms. CRC was ranked highly among TMAO-related disease retrieved from both EINs (top 0.02%, #1 out of 4,372 diseases retrieved based on Mendelian genetics and top 10.9% among 882 diseases based on genome-wide association genetics), providing strong supporting evidence for our hypothesis that TMAO is genetically related to CRC. We have also identified putative genetic pathways that may link TMAO to CRC, which warrants further investigation. Through systematic disease enrichment analysis, we also demonstrated that TMAO is related to metabolic syndromes and cancers in general.ConclusionsOur genome-wide analysis demonstrates that systems approaches to studying the epigenetic interactions among diet, microbiome metabolisms, and disease genetics hold promise for understanding disease pathogenesis. Our results show that TMAO is genetically associated with CRC. This study suggests that TMAO may be an important intermediate marker linking dietary meat and fat and gut microbiota metabolism to risk of CRC, underscoring opportunities for the development of new gut microbiome-dependent diagnostic tests and therapeutics for CRC.DP2HD084068/DP/NCCDPHP CDC HHS/United StatesR25 CA094186-06/CA/NCI NIH HHS/United StatesUL1 RR024989/RR/NCRR NIH HHS/United States26100814PMC447441

BMC Genomics

BackgroundThe contribution of alternative splicing and isoform expression to cellular response is emerging as an area of considerable interest, and the newly developed exon arrays allow for systematic study of these processes. We use this pilot study to report on the feasibility of exon array implementation looking to replace the 3' in vitro transcription expression arrays in our laboratory.ResultsPeripheral blood mononuclear cells form healthy donors were activated using phytohemagglutinin, IL2 and ionomycin and harvested at 5 points over a 7 day period. Flow cytometry measured cell cycle events and the Affymetrix exon array platform was used to identify the gene expression and alternate exon usage changes. Gene expression changes were noted in a total of 2105 transcripts, and alternate exon usage identified in 472 transcript clusters. There was an overlap of 263 transcripts which showed both differential expression and alternate exon usage over time. Gene ontology enrichment analysis showed a broader range of biological changes in biological processes for the differentially expressed genes, which include cell cycle, cell division, cell proliferation, chromosome segregation, cell death, component organization and biogenesis and metabolic process ontologies. The alternate exon usage ontological enrichments are in metabolism and component organization and biogenesis. We focus on alternate exon usage changes in the transcripts of the spliceosome complex. The real-time PCR validation rates were 86% for transcript expression and 71% for alternate exon usage.ConclusionsThis study illustrates that the Exon array technology has the potential to provide information on both transcript expression and isoform usage, with very little increase in expense

BMC Genomics

BackgroundFirst pass methods based on BLAST match are commonly used as an initial step to separate the different phylogenetic histories of genes in microbial genomes, and target putative horizontal gene transfer (HGT) events. This will continue to be necessary given the rapid growth of genomic data and the technical difficulties in conducting large-scale explicit phylogenetic analyses. However, these methods often produce misleading results due to their inability to resolve indirect phylogenetic links and their vulnerability to stochastic events.ResultsA new computational method of rapid, exhaustive and genome-wide detection of HGT was developed, featuring the systematic analysis of BLAST hit distribution patterns in the context of a priori defined hierarchical evolutionary categories. Genes that fall beyond a series of statistically determined thresholds are identified as not adhering to the typical vertical history of the organisms in question, but instead having a putative horizontal origin. Tests on simulated genomic data suggest that this approach effectively targets atypically distributed genes that are highly likely to be HGT-derived, and exhibits robust performance compared to conventional BLAST-based approaches. This method was further tested on real genomic datasets, including Rickettsia genomes, and was compared to previous studies. Results show consistency with currently employed categories of HGT prediction methods. In-depth analysis of both simulated and real genomic data suggests that the method is notably insensitive to stochastic events such as gene loss, rate variation and database error, which are common challenges to the current methodology. An automated pipeline was created to implement this approach and was made publicly available at: https://github.com/DittmarLab/HGTector. The program is versatile, easily deployed, has a low requirement for computational resources.ConclusionsHGTector is an effective tool for initial or standalone large-scale discovery of candidate HGT-derived genes.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-717) contains supplementary material, which is available to authorized users

BMC Genomics

BackgroundNext-generation sequencing (NGS) allows for sampling numerous viral variants from infected patients. This provides a novel opportunity to represent and study the mutational landscape of Hepatitis C Virus (HCV) within a single host.ResultsIntra-host variants of the HCV E1/E2 region were extensively sampled from 58 chronically infected patients. After NGS error correction, the average number of reads and variants obtained from each sample were 3202 and 464, respectively. The distance between each pair of variants was calculated and networks were created for each patient, where each node is a variant and two nodes are connected by a link if the nucleotide distance between them is 1. The work focused on large components having > 5% of all reads, which in average account for 93.7% of all reads found in a patient.ConclusionsMost intra-host variants are organized into distinct single-mutation components that are: well separated from each other, represent genetic distances between viral variants, robust to sampling, reproducible and likely seeded during transmission events. Facilitated by NGS, large components offer a novel evolutionary framework for genetic analysis of intra-host viral populations and understanding transmission, immune escape and drug resistance

BMC Genomics

BackgroundThe switch from photosynthetic or predatory to parasitic life strategies by apicomplexans is accompanied with a reductive evolution of genomes and losses of metabolic capabilities. Cryptosporidium is an extreme example of reductive evolution among apicomplexans, with losses of both the mitosome genome and many metabolic pathways. Previous observations on reductive evolution were largely based on comparative studies of various groups of apicomplexans. In this study, we sequenced two divergent Cryptosporidium species and conducted a comparative genomic analysis to infer the reductive evolution of metabolic pathways and differential evolution of invasion-related proteins within the Cryptosporidium lineage.ResultsIn energy metabolism, Cryptosporidium species differ from each other mostly in mitosome metabolic pathways. Compared with C. parvum and C. hominis, C. andersoni possesses more aerobic metabolism and a conventional electron transport chain, whereas C. ubiquitum has further reductions in ubiquinone and polyisprenoid biosynthesis and has lost both the conventional and alternative electron transport systems. For invasion-associated proteins, similar to C. hominis, a reduction in the number of genes encoding secreted MEDLE and insulinase-like proteins in the subtelomeric regions of chromosomes 5 and 6 was also observed in C. ubiquitum and C. andersoni, whereas mucin-type glycoproteins are highly divergent between the gastric C. andersoni and intestinal Cryptosporidium species.ConclusionsResults of the study suggest that rapidly evolving mitosome metabolism and secreted invasion-related proteins could be involved in tissue tropism and host specificity in Cryptosporidium spp. The finding of progressive reduction in mitosome metabolism among Cryptosporidium species improves our knowledge of organelle evolution within apicomplexans.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3343-5) contains supplementary material, which is available to authorized users.2016-12-08T00:00:00Z27931183PMC514689

BMC Genomics

BackgroundGenomic regions repressed for DNA replication, resulting in either delayed replication in S phase or underreplication in polyploid cells, are thought to be controlled by inhibition of replication origin activation. Studies in Drosophila polytene cells, however, raised the possibility that impeding replication fork progression also plays a major role.ResultsWe exploited genomic regions underreplicated (URs) with tissue specificity in Drosophila polytene cells to analyze mechanisms of replication repression. By localizing the Origin Recognition Complex (ORC) in the genome of the larval fat body and comparing this to ORC binding in the salivary gland, we found that sites of ORC binding show extensive tissue specificity. In contrast, there are common domains nearly devoid of ORC in the salivary gland and fat body that also have reduced density of ORC binding sites in diploid cells. Strikingly, domains lacking ORC can still be replicated in some polytene tissues, showing absence of ORC and origins is insufficient to repress replication. Analysis of the width and location of the URs with respect to ORC position indicates that whether or not a genomic region lacking ORC is replicated is controlled by whether replication forks formed outside the region are inhibited.ConclusionsThese studies demonstrate that inhibition of replication fork progression can block replication across genomic regions that constitutively lack ORC. Replication fork progression can be inhibited in both tissue-specific and genome region-specific ways. Consequently, when evaluating sources of genome instability it is important to consider altered control of replication forks in response to differentiation.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4992-3) contains supplementary material, which is available to authorized users.HG004279/National Human Genome Research Institute/U01 HG004279/HG/NHGRI NIH HHS/United StatesGM118098/National Institute of General Medical Sciences/GM57940/National Institute of General Medical Sciences/R35 GM118098/GM/NIGMS NIH HHS/United States2018-08-22T00:00:00Z30134926PMC610388

BMC Genomics

BackgroundPoxviruses constitute one of the largest and most complex animal virus families known. The notorious smallpox disease has been eradicated and the virus contained, but its simian sister, monkeypox is an emerging, untreatable infectious disease, killing 1 to 10\ua0% of its human victims. In the case of poxviruses, the emergence of monkeypox outbreaks in humans and the need to monitor potential malicious release of smallpox virus requires development of methods for rapid virus identification. Whole-genome sequencing (WGS) is an emergent technology with increasing application to the diagnosis of diseases and the identification of outbreak pathogens. But \u201cfinishing\u201d such a genome is a laborious and time-consuming process, not easily automated. To date the large, complete poxvirus genomes have not been studied comprehensively in terms of applying WGS techniques and evaluating genome assembly algorithms.ResultsTo explore the limitations to finishing a poxvirus genome from short reads, we first analyze the repetitive regions in a monkeypox genome and evaluate genome assembly on the simulated reads. We also report on procedures and insights relevant to the assembly (from realistically short reads) of genomes. Finally, we propose a neural network method (namely Neural-KSP) to \u201cfinish\u201d the process by closing gaps remaining after conventional assembly, as the final stage in a protocol to elucidate clinical poxvirus genomic sequences.ConclusionsThe protocol may prove useful in any clinical viral isolate (regardless if a reference-strain sequence is available) and especially useful in genomes confounded by many global and local repetitive sequences embedded in them. This work highlights the feasibility of finishing real, complex genomes by systematically analyzing genetic characteristics, thus remedying existing assembly shortcomings with a neural network method. Such finished sequences may enable clinicians to track genetic distance between viral isolates that provides a powerful epidemiological tool.2016-08-31T00:00:00Z27585810PMC50095261119