Bioinformatics Workflows for Genomic Variant Discovery, Interpretation and Prioritization

Next-generation sequencing (NGS) techniques allow high-throughput detection of a vast amount of variations in a cost-efficient manner. However, there still are inconsistencies and debates about how to process and analyse this ‘big data’. To accurately extract clinically relevant information from genomics data, choosing appropriate tools, knowing how to best utilize them and interpreting the results correctly is crucial. This chapter reviews state-of-the-art bioinformatics approaches in clinically relevant genomic variant detection. Best practices of reads-to-variant discovery workflows for germline and somatic short genomic variants are presented along with the most commonly utilized tools for each step. Additionally, methods for detecting structural variations are overviewed. Finally, approaches and current guidelines for clinical interpretation of genomic variants are discussed. As emphasized in this chapter, data processing and variant discovery steps are relatively well-understood. The differences in prioritization algorithms on the other hand can be perplexing, thus creating a bottleneck during interpretation. This review aims to shed light on the pros and cons of these differences to help experts give more informed decisions

The Parametric Design of a Photovoltaic Power System over a Parking Lot

The effective planning of urban areas is important in terms of improving both the urban density and the traffic problem. Parking lots should be arranged to manage spaces and traffic at the points where the population is highly dense. On the other hand, installing rooftop solar energy plants over parking lots are highly advantageous in terms of renewable energy production. During the design process of such urban power plants, the area-energy optimization and the shading caused by surrounding buildings have direct effect on overall performance. In this study, firstly a parking lot was designed on an empty parcel within the urban area of İzmir province, with the capacity of 1.704 vehicles, 64 motorcycles and 64 electric vehicle charging stations. In addition, a solar power plant was planned over the parking lot canopies, then a power system was designed by selecting the proper photovoltaic panels and inverters. On the parametric simulation software, which was used to determine the system performance, the solar radiation and shadow simulations on the designed parking lot were run. After that, the electricity generation performances were investigated and comparisons between the parking lot parcels and the selected dates were made. In the conclusion, it was found that 7.006 photovoltaic panels placed over the canopies with an area of 24.995 m2 are able to generate 8.084 MWh/year electricity

PANACEA: network-based methods for pharmacotherapy prioritization in personalized oncology

MOTIVATION: Identifying appropriate pharmacotherapy options from genomics results is a significant challenge in personalized oncology. However, computational methods for prioritizing drugs are underdeveloped. With the hypothesis that network-based approaches can improve the performance by extending the use of potential drug targets beyond direct interactions, we devised two network-based methods for personalized pharmacotherapy prioritization in cancer. RESULTS: We developed novel personalized drug prioritization approaches, PANACEA: PersonAlized Network-based Anti-Cancer therapy EvaluAtion. In PANACEA, initially, the protein interaction network is extended with drugs, and a driverness score is assigned to each altered gene. For scoring drugs, either (i) the ‘distance-based’ method, incorporating the shortest distance between drugs and altered genes, and driverness scores, or (ii) the ‘propagation’ method involving the propagation of driverness scores via a random walk with restart framework is performed. We evaluated PANACEA using multiple datasets, and demonstrated that (i) the top-ranking drugs are relevant for cancer pharmacotherapy using TCGA data; (ii) drugs that cancer cell lines are sensitive to are identified using GDSC data; and (iii) PANACEA can perform adequately in the clinical setting using cases with known drug responses. We also illustrate that the proposed methods outperform iCAGES and PanDrugs, two previous personalized drug prioritization approaches. AVAILABILITY AND IMPLEMENTATION: The corresponding R package is available on GitHub. (https://github.com/egeulgen/PANACEA.git). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Clinical, Electrodiagnostic, and Genetic Features of Tangier Disease in an Adolescent Girl with Presentation of Peripheral Neuropathy

WOS: 000365348100010PubMed ID: 26479764Tangier disease (TD) is a rare, autosomal recessive inherited disorder caused by a mutation in the adenosine triphosphate-binding cassette transporter 1 (ABCA1) gene, which results in a decrease in plasma high-density lipoprotein (HDL) levels. Peripheral neuropathy can be seen in approximately 50% of patients with TD, which usually occurs after the age of 15 years, and is characterized by relapsing-remitting mono-or polyneuropathy or syringomyelia-like neuropathy. Herein, we report a 16-year-old female patient who was initially diagnosed with peripheral neuropathy at the age of 13 years. Whole exome sequencing was performed, and a nonsense mutation (p.Arg1817X) in ABCA1 was identified. The patient was investigated for systemic findings of TD after the genetic diagnosis was made, and low (<5 mg/dL) levels of HDL cholesterol were detected by lipid electrophoresis. Other family members were reexamined after the diagnosis of the proband, and asymptomatic sister of the proband was diagnosed with TD. We would like to emphasize that TD should be considered in the differential diagnosis of pediatric patients presenting with peripheral neuropathy; furthermore detection of HDL levels by lipid electrophoresis is a simple but indicative diagnostic test

Investigation of multiple sclerosis-related pathways through the integration of genomic and proteomic data

Background. Multiple sclerosis (MS) has a complex pathophysiology, variable clinical presentation, and unpredictable prognosis; understanding the underlying mechanisms requires combinatorial approaches that warrant the integration of diverse molecular omics data. Methods. Here, we combined genomic and proteomic data of the same individuals among a Turkish MS patient group to search for biologically important networks. We previously identified differentially-expressed proteins by cerebrospinal fluid proteome analysis of 179 MS patients and 42 non-MS controls. Among this study group, 11 unrelated MS patients and 60 independent, healthy controls were subjected to whole-genome SNP genotyping, and genome-wide associations were assessed. Pathway enrichment analyses of MS-associated SNPs and differentially-expressed proteins were conducted using the functional enrichment tool, PANOGA. Results. Nine shared pathways were detected between the genomic and proteomic datasets after merging and clustering the enriched pathways. Complement and coagulation cascade was the most significantly associated pathway (hsa04610, P = 6.96x10-30). Other pathways involved in neurological or immunological mechanisms included adherens junctions (hsa04520, P = 6.64 x 10-25), pathogenic Escherichia coli infection (hsa05130, P = 9.03 x 10-14), prion diseases (hsa05020, P = 5.13 x 10-13). Conclusion. We conclude that integrating multiple datasets of the same patients helps reducing false negative and positive results of genome-wide SNP associations and highlights the most prominent cellular players among the complex pathophysiological mechanisms

ALPK3 gene mutation in a patient with congenital cardiomyopathy and dysmorphic features

WOS: 000450930400006PubMed ID: 28630369Primary cardiomyopathy is one of the most common inherited cardiac diseases and harbors significant phenotypic and genetic heterogeneity. Because of this, genetic testing has become standard in treatment of this disease group. Indeed, in recent years, next-generation DNA sequencing has found broad applications in medicine, both as a routine diagnostic tool for genetic disorders and as a high-throughput discovery tool for identifying novel disease-causing genes. We describe a male infant with primary dilated cardiomyopathy who was diagnosed using intrauterine echocardiography and found to progress to hypertrophic cardiomyopathy after birth. This proband was born to a nonconsanguineous family with a past history of a male fetus that died because of cardiac abnormalities at 30 wk of gestation. Using whole-exome sequencing, a novel homozygous frameshift mutation (c.2018delC; p.GIn675SerfsX30) in ALPK3 was identified and confirmed with Sanger sequencing. Heterozygous family members were normal with echocardiographic examination. To date, only two studies have reported homozygous pathogenic variants of ALPK3, with a total of seven affected individuals with cardiomyopathy from four unrelated consanguineous families. We include a discussion of the patient's phenotypic features and a review of relevant literature findings.Yale Program on Neurogenetics; Yale Center for Mendelian Disorders [U54HG006504]; National Institutes of Health (NIH) Medical Scientist Training Program [T32GM007205]; Gregory M. Kiez and Mehmet Kutman FoundationThis work was supported by the Yale Program on Neurogenetics and the Yale Center for Mendelian Disorders (U54HG006504), the National Institutes of Health (NIH) Medical Scientist Training Program Grant T32GM007205, and the Gregory M. Kiez and Mehmet Kutman Foundation (M.G.)

Potential Marker Pathways in the Endometrium That May Cause Recurrent Implantation Failure

The aim of this prospective cohort study was to identify altered biologic processes in the endometrium that may be potential markers of receptive endometrium in patients with repeated implantation failure (RIF) as compared with fertile controls. The study was conducted in a university-affiliated in vitro fertilization (IVF) gynecology clinic and molecular biology and genetics laboratory. Healthy fertile controls (n = 24) and patients with RIF (n = 24) were recruited. Window of implantation gene profiling associated with RIF was performed. Six hundred forty-one differentially expressed genes were identified, and 44 pathways were found enriched. Upon clustering of the enriched pathways, 9 representative pathways were established. The important pathways that were identified included circadian rhythm, pathways in cancer, proteasome, complement and coagulation cascades, citrate cycle, adherens junction, immune system and inflammation, cell cycle, and renin-angiotensin system. The involvement of the circadian rhythm pathway and other related pathways may alter the endometrium's functioning to ultimately cause RIF. Furthermore, we found that the pathogenesis of RIF was multifaceted and that numerous processes were involved. We believe that a better understanding of the underlying mechanisms of RIF will ultimately give rise to better treatment opportunities and to better outcomes in IVF

Endometrial gene expression profiling of recurrent implantation failure after in vitro fertilization

Recurrent implantation failure (RIF) is diagnosed when good-quality embryos repeatedly fail to implant after transfer in several in vitro fertilization (IVF) treatment cycles. Different expression profiles in maternal mRNAs could be referring to many diseases including RIF. This study aimed to reveal significantly dysregulated selected genes expression between healthy fertile women and RIF patients in the implantation window days of the natural menstrual cycle. MME, WWC1, TNC, and FOXP3 genes were chosen as target genes regarding their possible relations with the implantation process. Pathways with these genes were identified and the relationship between these pathways and RIF was investigated. In this study, the endometrial biopsy samples were collected in the secretory phase (cycle day 20-24) of the menstrual cycle from RIF patients (n = 34) and healthy fertile controls (n = 34). After "Pathway and network-oriented GWAS analysis" (PANOGA) and "Kyoto Encyclopedia of Genes and Genomes" (KEGG) pathway analysis; "Membrane Metalloendopeptidase" (MME), "WW and C2 Domain Containing 1" (WWC1), "Tenascin C" (TNC) and "Forkhead Box P3" (FOXP3) genes were chosen as target genes by regarding their possible relation with implantation process. Detection of differences in mRNA expressions between the control group and RIF patients has been performed with the droplet digital PCR (ddPCR) method. Results of the study showed that MME and WWC1 genes expression levels are significantly (p < 0,05) up-regulated 4.9 and 5.2 times respectively and TNC gene expression level is significantly (p < 0,05) down-regulated 9 times in the RIF samples compared to the control group. However, no statistically significant difference was observed between the patient group and the control group in the expression of the FOXP3 gene (p < 0.05). Changes are observed in the expression of the renin-angiotensin system pathway in which the MME gene is involved in the implantation process. The increase in MME gene expression can be speculated to cause implantation failure by restricting the invasion of trophoblast cells. Increasing WWC1 gene expression in the Hippo signaling pathway inhibits "Yes-associated protein 1" (YAP) expression, which is a transcriptional cofactor. Inhibition of YAP protein expression may impair the implantation process by causing the failure of endometrial decidualization. The TNC gene is located in the focal adhesion pathway and this pathway reduces cell adhesion on the endometrial surface to facilitate the attachment of the embryo to the endometrium. The reason for implantation failure might be that the intercellular connections are not suitable for implantation as a result of decreased expression of the focal adhesion pathway in which the TNC gene is effective. Considering the relations between the pathways of the target genes and the implantation process, changes in the expression of target genes might be a cause of RIF