Genomic Coordinates Research Articles

ORIO (Online Resource for Integrative Omics): a web-based platform for rapid integration of next generation sequencing data.

Established and emerging next generation sequencing (NGS)-based technologies allow for genome-wide interrogation of diverse biological processes. However, accessibility of NGS data remains a problem, and few user-friendly resources exist for integrative analysis of NGS data from different sources and experimental techniques. Here, we present Online Resource for Integrative Omics (ORIO; https://orio.niehs.nih.gov/), a web-based resource with an intuitive user interface for rapid analysis and integration of NGS data. To use ORIO, the user specifies NGS data of interest along with a list of genomic coordinates. Genomic coordinates may be biologically relevant features from a variety of sources, such as ChIP-seq peaks for a given protein or transcription start sites from known gene models. ORIO first iteratively finds read coverage values at each genomic feature for each NGS dataset. Data are then integrated using clustering-based approaches, giving hierarchical relationships across NGS datasets and separating individual genomic features into groups. In focusing its analysis on read coverage, ORIO makes limited assumptions about the analyzed data; this allows the tool to be applied across data from a variety of experiments and techniques. Results from analysis are presented in dynamic displays alongside user-controlled statistical tests, supporting rapid statistical validation of observed results. We emphasize the versatility of ORIO through diverse examples, ranging from NGS data quality control to characterization of enhancer regions and integration of gene expression information. Easily accessible on a public web server, we anticipate wide use of ORIO in genome-wide investigations by life scientists.

The Proteins API: accessing key integrated protein and genome information.

The Proteins API provides searching and programmatic access to protein and associated genomics data such as curated protein sequence positional annotations from UniProtKB, as well as mapped variation and proteomics data from large scale data sources (LSS). Using the coordinates service, researchers are able to retrieve the genomic sequence coordinates for proteins in UniProtKB. This, the LSS genomics and proteomics data for UniProt proteins is programmatically only available through this service. A Swagger UI has been implemented to provide documentation, an interface for users, with little or no programming experience, to ‘talk’ to the services to quickly and easily formulate queries with the services and obtain dynamically generated source code for popular programming languages, such as Java, Perl, Python and Ruby. Search results are returned as standard JSON, XML or GFF data objects. The Proteins API is a scalable, reliable, fast, easy to use RESTful services that provides a broad protein information resource for users to ask questions based upon their field of expertise and allowing them to gain an integrated overview of protein annotations available to aid their knowledge gain on proteins in biological processes. The Proteins API is available at (http://www.ebi.ac.uk/proteins/api/doc).

MP82-08 THE POTENTIAL OF 2 MICRORNA CLUSTERS IN ELUCIDATION OF BIOLOGICAL FUNCTIONS OF SIGNALLING PATHWAYS REGULATED BY MICRORNAS IN UNDERACTIVE BLADDER

You have accessJournal of UrologyUrodynamics/Lower Urinary Tract Dysfunction/Female Pelvic Medicine: Basic Research & Pathophysiology II1 Apr 2017MP82-08 THE POTENTIAL OF 2 MICRORNA CLUSTERS IN ELUCIDATION OF BIOLOGICAL FUNCTIONS OF SIGNALLING PATHWAYS REGULATED BY MICRORNAS IN UNDERACTIVE BLADDER Ali Hashemi Gheinani, Fiona C. Burkhard, and Katia Monastyrskaya Ali Hashemi GheinaniAli Hashemi Gheinani More articles by this author , Fiona C. BurkhardFiona C. Burkhard More articles by this author , and Katia MonastyrskayaKatia Monastyrskaya More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.2555AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES MicroRNAs regulate diverse biological processes. Previously we identified miRNA-regulated pathways in bladder outlet obstruction (BOO)-induced bladder dysfunction. MiRNAs in a cluster reside in genomic proximity (<10 kb) and their expression might be mediated by common transcription factors. Here we probed functional associations of BOO phenotype-specific miRNAs and identified several co-expressed miRNA sub-networks. METHODS MiRNA sequences and genomic coordinates were extracted from miRBase version 21. Large scale chromosomal mapping of human miRNA structural clusters was done using MIReStruC-1.0 package. Next-generation sequencing datasets of patients′ biopsies with urodynamically established BOO with and without detrusor overactivity (DO and BO groups, respectively) or with detrusor underactivity (UA group) were used to perform miRNA-mRNA integrated analysis and target pairing. Sequences were aligned with MAFFT version 7 and Clustal X 2.1 and manually refined with RALEE-RNA version 0.8. RESULTS In DO group hsa-miR-376c-3p/hsa-miR-409-3p cluster was identified on chromosome 14. In BO group hsa-miR-889-3p/hsa-miR-410-3p/hsa-miR-409-3p cluster was detected on chromosome 14. Three miRNA clusters were detected in UA group: hsa-miR-25-3p/hsa-miR-106b-3p cluster on chromosome 7, and 2 clusters on chromosome 1: hsa-miR-199a-3p/hsa-miR-3120-3p cluster and hsa-miR-429/hsa-miR-200b-3p cluster belonging to miR-200bc/429/548a family. Integrated miRNA-mRNA expression profiling revealed no significant target overlap, and 90% of targets of up-regulated miRNA clusters were also up-regulated. No major contribution of the miRNA clusters to the biological functions of miRNA-regulated pathways was detected in DO and BO groups. In UA group 2 down-regulated hsa-miR-199a-3p/hsa-miR-3120-3p and hsa-miR-429/hsa-miR-200b-3p miRNA clusters were necessary and sufficient to determine the functions of all miRNA-regulated pathways and their targets constituted the majority of miRNA-regulated pathway elements. CONCLUSIONS Multiple co-expressed miRNAs may cooperatively influence biological processes and the acontractile urodynamic phenotype in the underactive bladder. Elucidating the down-regulation mechanisms of these miRNA clusters may help determine the »point of no return« for the loss of bladder function during BOO. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e1100 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Ali Hashemi Gheinani More articles by this author Fiona C. Burkhard More articles by this author Katia Monastyrskaya More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Principles and Recommendations for Standardizing the Use of the Next-Generation Sequencing Variant File in Clinical Settings

A national workgroup convened by the Centers for Disease Control and Prevention identified principles and made recommendations for standardizing the description of sequence data contained within the variant file generated during the course of clinical next-generation sequence analysis for diagnosing human heritable conditions. The specifications for variant files were initially developed to be flexible with regard to content representation to support a variety of research applications. This flexibility permits variation with regard to how sequence findings are described and this depends, in part, on the conventions used. For clinical laboratory testing, this poses a problem because these differences can compromise the capability to compare sequence findings among laboratories to confirm results and to query databases to identify clinically relevant variants. To provide for a more consistent representation of sequence findings described within variant files, the workgroup made several recommendations that considered alignment to a common reference sequence, variant caller settings, use of genomic coordinates, and gene and variant naming conventions. These recommendations were considered with regard to the existing variant file specifications presently used in the clinical setting. Adoption of these recommendations is anticipated to reduce the potential for ambiguity in describing sequence findings and facilitate the sharing of genomic data among clinical laboratories and other entities.

A recurrent mutation in bone morphogenetic proteins-2-inducible kinase gene is associated with developmental dysplasia of the hip.

Developmental dysplasia of the hip (DDH) is a complex disorder of the hip joint affecting 1-5‰ of newborns. While genetic influence on DDH has been long known, DDH has not been ascribed to any specific genetic event. The present study reported on variants contributing to DDH susceptibility in a family with four individuals affected across three generations. Whole-exome sequencing was performed in three affected and two unaffected individuals of a pedigree with DDH. Candidate variants were confirmed by Sanger sequencing and then validated in available family members and 37 sporadic DDH patients. Two novel heterozygous, inframe mutations causing multi-nucleotide substitution polymorphisms (c.1432_1440delCAGCAGCAG corresponding with p.Gln478_480del and c.1440_1441insCAG corresponding with p.Gln480ins) in exon 11 of chromosome 4 in bone morphogenetic proteins-2-inducible kinase (BMP2K) were identified; these were found in members of the pedigree affected by DDH and in the unaffected grandmother of the proband, who was deemed to be the carrier of potential mutations, but not in the unaffected normal control saunt of the proband. These two variants shared the same genomic coordinate but with different types of mutation in BMP2K. BMP2K is known to be associated with bone and cartridge development and heterozygous mutations were found to be present in 4/4 (100%) of the affected family members, 4/15 (26.7%) of the unaffected family members and 0/7 (0%) of the unaffected unrelated family members. Genotyping of 37 unrelated, sporadic DDH patients showed that three cases were positive for the BMP2K c.1432_1440delCAGCAGCAG variants (8.12%). These findings provided strong evidence for the role of BMP2K variants in causing DDH and demonstrated that the combination of pedigree information and next-generation sequencing is an effective method for identifying pathogenic sites associated with DDH.

Extending the use of GWAS data by combining data from different genetic platforms.

BackgroundIn the past decade many Genome-wide Association Studies (GWAS) were performed that discovered new associations between single-nucleotide polymorphisms (SNPs) and various phenotypes. Imputation methods are widely used in GWAS. They facilitate the phenotype association with variants that are not directly genotyped. Imputation methods can also be used to combine and analyse data genotyped on different genotyping arrays. In this study we investigated the imputation quality and efficiency of two different approaches of combining GWAS data from different genotyping platforms. We investigated whether combining data from different platforms before the actual imputation performs better than combining the data from different platforms after imputation.MethodsIn total 979 unique individuals from the AMC-PAS cohort were genotyped on 3 different platforms. A total of 706 individuals were genotyped on the MetaboChip, a total of 757 individuals were genotyped on the 50K gene-centric Human CVD BeadChip, and a total of 955 individuals were genotyped on the HumanExome chip. A total of 397 individuals were genotyped on all 3 individual platforms. After pre-imputation quality control (QC), Minimac in combination with MaCH was used for the imputation of all samples with the 1,000 genomes reference panel. All imputed markers with an r2 value of <0.3 were excluded in our post-imputation QC.ResultsA total of 397 individuals were genotyped on all three platforms. All three datasets were carefully matched on strand, SNP ID and genomic coordinates. This resulted in a dataset of 979 unique individuals and a total of 258,925 unique markers. A total of 4,117,036 SNPs were available when imputation was performed before merging the three datasets. A total of 3,933,494 SNPs were available when imputation was done on the combined set. Our results suggest that imputation of individual datasets before merging performs slightly better than after combining the different datasets.ConclusionsImputation of datasets genotyped by different platforms before merging generates more SNPs than imputation after putting the datasets together.

The Pancreatic Islet Regulome Browser

The pancreatic islet is a highly specialized tissue embedded in the exocrine pancreas whose primary function is that of controlling glucose homeostasis. Thus, understanding the transcriptional control of islet-cell may help to puzzle out the pathogenesis of glucose metabolism disorders. Integrative computational analyses of transcriptomic and epigenomic data allows predicting genomic coordinates of putative regulatory elements across the genome and, decipher tissue-specific functions of the non-coding genome. We herein present the Islet Regulome Browser, a tool that allows fast access and exploration of pancreatic islet epigenomic and transcriptomic data produced by different labs worldwide. The Islet Regulome Browser is now accessible on the internet or may be installed locally. It allows uploading custom tracks as well as providing interactive access to a wealth of information including Genome-Wide Association Studies (GWAS) variants, different classes of regulatory elements, together with enhancer clusters, stretch-enhancers and transcription factor binding sites in pancreatic progenitors and adult human pancreatic islets. Integration and visualization of such data may allow a deeper understanding of the regulatory networks driving tissue-specific transcription and guide the identification of regulatory variants. We believe that such tool will facilitate the access to pancreatic islet public genomic datasets providing a major boost to functional genomics studies in glucose metabolism related traits including diabetes.

A variant by any name: quantifying annotation discordance across tools and clinical databases

BackgroundClinical genomic testing is dependent on the robust identification and reporting of variant-level information in relation to disease. With the shift to high-throughput sequencing, a major challenge for clinical diagnostics is the cross-identification of variants called on their genomic position to resources that rely on transcript- or protein-based descriptions.MethodsWe evaluated the accuracy of three tools (SnpEff, Variant Effect Predictor, and Variation Reporter) that generate transcript and protein-based variant nomenclature from genomic coordinates according to guidelines by the Human Genome Variation Society (HGVS). Our evaluation was based on transcript-controlled comparisons to a manually curated set of 126 test variants of various types drawn from data sources, each with HGVS-compliant transcript and protein descriptors. We further evaluated the concordance between annotations generated by Snpeff and Variant Effect Predictor and those in major germline and cancer databases: ClinVar and COSMIC, respectively.ResultsWe find that there is substantial discordance between the annotation tools and databases in the description of insertions and/or deletions. Using our ground truth set of variants, constructed specifically to identify challenging events, accuracy was between 80 and 90% for coding and 50 and 70% for protein changes for 114 to 126 variants. Exact concordance for SNV syntax was over 99.5% between ClinVar and Variant Effect Predictor and SnpEff, but less than 90% for non-SNV variants. For COSMIC, exact concordance for coding and protein SNVs was between 65 and 88% and less than 15% for insertions. Across the tools and datasets, there was a wide range of different but equivalent expressions describing protein variants.ConclusionsOur results reveal significant inconsistency in variant representation across tools and databases. While some of these syntax differences may be clear to a clinician, they can confound variant matching, an important step in variant classification. These results highlight the urgent need for the adoption and adherence to uniform standards in variant annotation, with consistent reporting on the genomic reference, to enable accurate and efficient data-driven clinical care.

Next Generation Sequencing for Blood Group Antigen Profiling

There are over 300 serologically defined red blood cell (RBC) antigens and 33 serologically defined platelet antigens, most of which have known genetic changes in 45 RBC or 6 platelet genes that correlate with antigen expression. Exposure to non-self RBC antigens during transfusion or pregnancy can lead to the development of alloantibodies, which on re-exposure can lead to clinically significant and even fatal complications. Therefore, it is vital to know which antigens are present on RBCs. However, traditional serologic phenotyping methods are labor intensive, costly, sometimes unreliable, and reagents are not always available. As such, routine antigen typing is only done for ABO and D antigens.A large percentage of blood is given for hematologic malignancies that will soon get routine whole genome sequencing (WGS). For a minor added cost this data could be used for RBC antigen prediction. However, there are no published reports of using WGS data to predict RBC antigens. This is likely for several reasons: (1) none of the existing WGS data sets have paired serologic RBC phenotypes, (2) there are no fully annotated and complete databases of genotypes to phenotypes, (3) all of the known alleles are defined using cDNAs numbered relative to the start codon without human genome coordinates, and (4) lack of software capable of automated RBC antigen prediction.We have created a fully interactive web site of all known blood group genotype to phenotype correlations, fully annotated with relevant information, and mapped to and visually overlaid to their corresponding human reference genome gene sequences, with algorithms to predict antigen phenotypes from inputted sequences. These predictions are part of the General Genome Reports for the 100 patients getting WGS as part of The MedSeq Project. In addition, each patient is undergoing an extensive antigen phenotypic workup using traditional blood bank serology and currently available SNP PCR based assays, which are being used to validate and improve our prediction strategies.As clinical WGS becomes pervasive we hope that comprehensive blood group prediction will be done on everyone, allowing for easy identification of rare donors and the prevention of alloantibody formation using extended upfront matching of antigens from sequenced recipients and donor. DisclosuresNo relevant conflicts of interest to declare.

Plastid: nucleotide-resolution analysis of next-generation sequencing and genomics data.

BackgroundNext-generation sequencing (NGS) informs many biological questions with unprecedented depth and nucleotide resolution. These assays have created a need for analytical tools that enable users to manipulate data nucleotide-by-nucleotide robustly and easily. Furthermore, because many NGS assays encode information jointly within multiple properties of read alignments ― for example, in ribosome profiling, the locations of ribosomes are jointly encoded in alignment coordinates and length ― analytical tools are often required to extract the biological meaning from the alignments before analysis. Many assay-specific pipelines exist for this purpose, but there remains a need for user-friendly, generalized, nucleotide-resolution tools that are not limited to specific experimental regimes or analytical workflows.ResultsPlastid is a Python library designed specifically for nucleotide-resolution analysis of genomics and NGS data. As such, Plastid is designed to extract assay-specific information from read alignments while retaining generality and extensibility to novel NGS assays. Plastid represents NGS and other biological data as arrays of values associated with genomic or transcriptomic positions, and contains configurable tools to convert data from a variety of sources to such arrays.Plastid also includes numerous tools to manipulate even discontinuous genomic features, such as spliced transcripts, with nucleotide precision. Plastid automatically handles conversion between genomic and feature-centric coordinates, accounting for splicing and strand, freeing users of burdensome accounting. Finally, Plastid’s data models use consistent and familiar biological idioms, enabling even beginners to develop sophisticated analytical workflows with minimal effort.ConclusionsPlastid is a versatile toolkit that has been used to analyze data from multiple NGS assays, including RNA-seq, ribosome profiling, and DMS-seq. It forms the genomic engine of our ORF annotation tool, ORF-RATER, and is readily adapted to novel NGS assays. Examples, tutorials, and extensive documentation can be found at https://plastid.readthedocs.io.

Transcription factor HIF1A: downstream targets, associated pathways, polymorphic hypoxia response element (HRE) sites, and initiative for standardization of reporting in scientific literature.

Hypoxia-inducible factor-1α (HIF-1α) has crucial role in adapting cells to hypoxia through expression regulation of many genes. Identification of HIF-1α target genes (HIF-1α-TGs) is important for understanding the adapting mechanism. The aim of the present study was to collect known HIF-1α-TGs and identify their associated pathways. Targets and associated genomics data were retrieved using PubMed, WoS ( http://apps.webofknowledge.com/ ), HGNC ( http://www.genenames.org/ ), NCBI ( http://www.ncbi.nlm.nih.gov/ ), Ensemblv.84 ( http://www.ensembl.org/index.html ), DAVID Bioinformatics Resources ( https://david.ncifcrf.gov /), and Disease Ontology database ( http://disease-ontology.org/ ). From 51 papers, we collected 98 HIF-1α TGs found to be associated with 20 pathways, including metabolism of carbohydrates and pathways in cancer. Reanalysis of genomic coordinates of published HREs (hypoxia response elements) revealed six polymorphisms within HRE sites (HRE-SNPs): ABCG2, ACE, CA9, and CP. Due to large heterogeneity of results presentation in scientific literature, we also propose a first step towards reporting standardization of HIF-1α-target interactions consisting of ten relevant data types. Suggested minimal checklist for reporting will enable faster development of a complete catalog of HIF-1α-TGs, data sharing, bioinformatics analyses, and setting novel more targeted hypotheses. The proposed format for data standardization is not yet complete but presents a baseline for further optimization of the protocol with additional details, for example, regarding the experimental validation.

G23D: Online tool for mapping and visualization of genomic variants on 3D protein structures.

BackgroundEvaluation of the possible implications of genomic variants is an increasingly important task in the current high throughput sequencing era. Structural information however is still not routinely exploited during this evaluation process. The main reasons can be attributed to the partial structural coverage of the human proteome and the lack of tools which conveniently convert genomic positions, which are the frequent output of genomic pipelines, to proteins and structure coordinates.ResultsWe present G23D, a tool for conversion of human genomic coordinates to protein coordinates and protein structures. G23D allows mapping of genomic positions/variants on evolutionary related (and not only identical) protein three dimensional (3D) structures as well as on theoretical models. By doing so it significantly extends the space of variants for which structural insight is feasible. To facilitate interpretation of the variant consequence, pathogenic variants, functional sites and polymorphism sites are displayed on protein sequence and structure diagrams alongside the input variants. G23D also provides modeling of the mutant structure, analysis of intra-protein contacts and instant access to functional predictions and predictions of thermo-stability changes. G23D is available at http://www.sheba-cancer.org.il/G23D.ConclusionsG23D extends the fraction of variants for which structural analysis is applicable and provides better and faster accessibility for structural data to biologists and geneticists who routinely work with genomic information.

Genome-wide recruitment profiling of transcription factor Crz1 in response to high pH stress.

BackgroundExposure of the budding Saccharomyces cerevisiae to an alkaline environment produces a robust transcriptional response involving hundreds of genes. Part of this response is triggered by an almost immediate burst of calcium that activates the Ser/Thr protein phosphatase calcineurin. Activated calcineurin dephosphorylates the transcription factor (TF) Crz1, which moves to the nucleus and binds to calcineurin/Crz1 responsive gene promoters. In this work we present a genome-wide study of the binding of Crz1 to gene promoters in response to high pH stress.ResultsEnvironmental alkalinization promoted a time-dependent recruitment of Crz1 to 152 intergenic regions, the vast majority between 1 and 5 min upon stress onset. Positional evaluation of the genomic coordinates combined with existing transcriptional studies allowed identifying 140 genes likely responsive to Crz1 regulation. Gene Ontology analysis confirmed the relevant impact of calcineurin/Crz1 on a set of genes involved in glucose utilization, and uncovered novel targets, such as genes responsible for trehalose metabolism. We also identified over a dozen of genes encoding TFs that are likely under the control of Crz1, suggesting a possible mechanism for amplification of the signal at the transcription level. Further analysis of the binding sites allowed refining the consensus sequence for Crz1 binding to gene promoters and the effect of chromatin accessibility in the timing of Crz1 recruitment to promoters.ConclusionsThe present work defines at the genomic-wide level the kinetics of binding of Crz1 to gene promoters in response to alkaline stress, confirms diverse previously known Crz1 targets and identifies many putative novel ones. Because of the relevance of calcineurin/Crz1 in signaling diverse stress conditions, our data will contribute to understand the transcriptional response in other circumstances that also involve calcium signaling, such as exposition to sexual pheromones or saline stress.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3006-6) contains supplementary material, which is available to authorized users.

Abstract 3612: Challenges in variant searching and annotation for clinical cancer testing

Abstract Cancer testing is undergoing a revolution. While small gene panels have previously dominated the landscape, whole exome (WES) based strategies have recently emerged as valuable tools for identifying mutations with clinical significance and are being rapidly adopted into routine clinical cancer care. Assessing the significance and actionability of these variants is largely dependent on the growth of public repositories of germline and somatic variants, such as ExAC, COSMIC, TCGA and ClinVar. However, efforts to integrate data from these various sources have revealed numerous challenges. One of these challenges is the generation and use of variant syntax in a standardized, unambiguous format, which is paramount for variant search for both the clinical and scientific community. Variants can be represented in many different ways: in the VCF file format, which is the de facto standard for sequencing data; in genomic or transcript-based coordinates using HGVS nomenclature; as amino acid alterations in three- or single-letter codes according to transcript and protein definitions that can vary based on the database used. Analyses of dbSNP and COSMIC identified at least 350,000 and 27,000 variants respectively that, without “normalization”, have ambiguous VCF representations (using software described by Tan et al., 2015). This indicates that one-to-one searches and annotations in VCF files may not identify an exact match in the absence of normalization. At the coding and protein level, variants are typically reported according to syntax recommendations by the Human Genome Variation Society (HGVS). In evaluating a number of tools for generating HGVS nomenclature (snpEff, VEP, and Variation Reporter), we found challenges in reconciling syntax representation across these tools and databases. We demonstrate that variant annotation is dependent on both transcript and version, complicating comparisons between NCBI and Ensembl-based systems, such as ClinVar (NCBI) and COSMIC (Ensembl). Even given the same transcript, variants can be represented differently. Over 20% of variants output by the tools in our comparison reported different nomenclature for the same exact variant reported by ClinVar. Using a manually curated ‘gold truth’ set of variants, we found that as many as 75% of non-missense variants are called incorrectly by these tools. The results of our tests have significant implications for the search and annotation of variants during cancer analyses and interpretation, and serve to inform the ongoing adoption and refinement of available resources. Citation Format: Jennifer Yen, Sarah Garcia, Michael Clark, Steve Chervitz, Brian Linebaugh, Aldrin Montana, John West, Richard Chen, Deanna Church. Challenges in variant searching and annotation for clinical cancer testing. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3612.

Abstract 5272: Cloud-based informatics enables the design and analysis of massively multiplex custom gene fusion panels for next-generation sequencing on FFPE RNA samples

Abstract Gene fusions, a combination of two genes, comprising their coding and/or regulatory sequences, are caused by structural rearrangements in DNA or in RNA transcripts. Many gene fusions are strong driver mutations in neoplasia, and are important in understanding basic biology, interaction with targeted therapy, and research into risk stratification and outcomes. Next-generation sequencing enables sensitive, specific and precise detection of particular fusion isoforms for defined gene pairs. Massively multiplex Ampliseq gene fusion assays enable enrichment of fusion transcripts using as little as 10 ng of RNA extracted from FFPE samples. Sequencing on Ion Torrent instruments reveals the full sequence of the gene fusion, for precise definition of the breakpoint and the expressed exons or promoter regions of both genes. We developed cloud-based software to support the design of a custom Ampliseq gene fusion panel, comprising 1 to 1,000 fusion isoform assays and any gene expression assays for normalization. We extensively mined the scientific literature on fusions and the COSMIC database to identify over 1000 fusion isoforms. We rigorously curated this data using automated and manual methods, including mapping, confirmation and correction of reported sequence to obtain genomic coordinates, identification of breakpoints, annotation of exon junctions, and selected wet lab testing. We created a database containing over 1000 high quality curated and annotated fusion isoforms, including 70 ALK, 60 RET, 26 ROS1, and 21 NTRK1 fusions. We designed Ampliseq primer pairs for each of these fusions using advanced assay design and pooling algorithms, such that all fusion and gene expression assays can be multiplexed into 1 or 2 compatible pools. Assays can be selected by gene or gene pair; detailed information about each assay selected includes isoform, genes, exon numbers, and links to COSMIC and to relevant publications. We developed cloud-based analysis software to analyze the BAM file resulting from amplification and sequencing of custom Ampliseq fusion panels on an Ion Torrent sequencer. This analysis leverages the rich annotation information from the assay design. The reads are mapped to a custom reference sequence tailored to the custom Ampliseq fusion assay, and applying an optimized algorithm to select confidently mapped reads based on read length and overlap with each gene of the gene pair based on the reference and annotated breakpoint. Gene fusions are detected based on the total number of fusion reads and optionally frequency, and on the properties of those reads. Software QC steps for total number of mapped reads, number of reads for gene expression controls, and elimination of cross-talk artifacts result in a highly sensitive and specific detection of fusions, with LOD below 1%. Fusion results for any or all samples can be viewed, annotated, filtered, and visualized, and exported. Citation Format: Fiona Hyland, Rajesh Gottimukkala, Efren Ballesteros, Heinz Breu, Yuandan Lou, Scott Myrand, Michael Hogan, Kelli Bramlett, Guoying Liu, Seth Sadis. Cloud-based informatics enables the design and analysis of massively multiplex custom gene fusion panels for next-generation sequencing on FFPE RNA samples. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5272.

A Survey of Software and Hardware Approaches to Performing Read Alignment in Next Generation Sequencing.

Computational genomics is an emerging field that is enabling us to reveal the origins of life and the genetic basis of diseases such as cancer. Next Generation Sequencing (NGS) technologies have unleashed a wealth of genomic information by producing immense amounts of raw data. Before any functional analysis can be applied to this data, read alignment is applied to find the genomic coordinates of the produced sequences. Alignment algorithms have evolved rapidly with the advancement in sequencing technology, striving to achieve biological accuracy at the expense of increasing space and time complexities. Hardware approaches have been proposed to accelerate the computational bottlenecks created by the alignment process. Although several hardware approaches have achieved remarkable speedups, most have overlooked important biological features, which have hampered their widespread adoption by the genomics community. In this paper, we provide a brief biological introduction to genomics and NGS. We discuss the most popular next generation read alignment tools and algorithms. Furthermore, we provide a comprehensive survey of the hardware implementations used to accelerate these algorithms.

48 - Getting to Know Your LCRs: Recognizing and Interpreting Atypical CNVs in Recurrent Syndromic Microdeletion/Duplication Regions Mediated by Alternative Low Copy Repeat Elements

Regions of the genome containing multiple low copy repeats (LCRs) are well known for recurrent deletions and duplications. The routine use of array-based technologies has expanded our understanding of the complexity and diversity of these recurrent rearrangements, historically detected by FISH. It is now clear that in addition to the common and clinically well-defined microdeletions/duplications, other CNVs in these regions are mediated by alternative LCRs. Interpretation of these atypical CNVs within regions of syndromic microdeletions/duplications is often challenging, especially when the critical genes for the phenotypes are not well defined. Additionally, identification of relevant patients from the medical literature can be cumbersome, as most historical papers refer to previously established LCR nomenclature rather than genomic coordinates. Additional care must be taken when reporting these results and referencing relevant literature, as there can be significant clinical differences between typical and atypical deletions/duplications. Focusing on genomic regions containing recurrent CNVs mediated by LCRs, we have curated .bed and .aed files to illustrate the position and conventional names of both common and atypical breakpoint LCRs in those regions. This allows for rapid recognition of typical and atypical deletions/duplications, and also provides an easy reference to both LCR nomenclature and current genomic coordinates. We will review the current clinical understanding of both typical and atypical CNVs in recurrent microdeletion/duplication regions (e.g. 22q11.2, 15q11.2-13, and 7q11.23), provide a collection of relevant literature to aid interpretations, and highlight the utility of this easy to use resource when interpreting typical and atypical recurrent LCR-mediated copy number variation.

TxCoords: A Novel Web Application for Transcriptomic Peak Re-Mapping.

Since the development of new technologies such as RIP-Seq and m6A-seq, peak calling has become an important step in transcriptomic sequencing data analysis. However, many of the reported genomic coordinates of transcriptomic peaks are incorrect owing to negligence of the introns. There is currently a lack of a convenient tool to address this problem. Here, we present txCoords, a novel and easy-to-use web application for transcriptomic peak re-mapping. txCoords can be used to correct the incorrectly reported transcriptomic peaks and retrieve the true sequences. It also supports visualization of the re-mapped peaks in a schematic figure or from the UCSC Genome Browser. Our web server is freely available at http://www.bioinfo.tsinghua.edu.cn/txCoords.

537. New Graph-Based Algorithm for Comprehensive Identification and Tracking Retroviral Integration Sites

Vector integration sites (IS) in hematopoietic stem cell (HSC) gene therapy (GT) applications are stable genetic marks, distinctive for each independent cell clone and its progeny. The characterization of IS allows to identify each cell clone and individually track its fate in different tissues or cell lineages and during time, and is required for assessing the safety and efficacy of the treatment. Bioinformatics pipelines for IS detection used in GT identify the sequence reads mapping in the same genomic position of the reference genome as a single IS but discard those ambiguously mapped in multiple genomic regions. The loss of such significant portion of patients’ IS may hide potential malignant events thus reducing the reliability of IS studies. We developed a novel tool that is able to accurately identify IS in any genomic region even if composed by repetitive genomic sequences. Our approach exploits an initial genome free analysis of sequencing reads by creating an undirected graph in which nodes are the input sequences and edges represent valid alignments (over a specific identity threshold) between pairs of nodes. Through the analysis and decomposition of the graph, the method identifies indivisible subgraphs of sequences (clusters), each of them corresponding to an IS. Once extracted the consensus sequence of the clusters and aligned on the reference genome, we collect the alignment results and the annotation labels from RepeatMasker. By combining the set of genomic coordinates and the annotation labels, the method retraces the initial sequence graph, statistically validates the clusters through permutation test and produces the final list of IS. We tested the reliability of our tool on 3 IS datasets generated from simulated sequencing reads with incremental rate of nucleotide variations (0%, 0.25% and 0.5%) and real data from a cell line with known IS and we compared out tool to VISPA and UClust, used for GT studies. In the simulated datasets our tool demonstrated precision and recall ranging 0.85-0.97 and 0.88-0.99 respectively, producing the aggregate F-score ranging 0.86-0.98 which resulted higher than VISPA and UClust. In the experimental case of sequences from LAM-PCR products, our tool and VISPA were able to identify all the 6 known ISs for >98% of the reads produced, while UClust identified only 5 out 6 ISs. We then used our tool to reanalyze the sequencing reads of our GT clinical trial for Metachromatic Leukodystrophy (MLD) completing the hidden portion of IS. The overall number of ISs, sequencing reads and estimated actively re-populating HSCs was increased by an average fold ~1.5 with respect the previously published data obtained through VISPA whereas the diversity index of the population did not change and no aberrant clones in repeats occurred. Our tool addresses and solves important open issues in retroviral IS identification and clonal tracking, allowing the generation of a comprehensive repertoire of IS.

E23D: database and visualization of A-to-I RNA editing sites mapped to 3D protein structures.

e23D, a database of A-to-I RNA editing sites from human, mouse and fly mapped to evolutionary related protein 3D structures, is presented. Genomic coordinates of A-to-I RNA editing sites are converted to protein coordinates and mapped onto 3D structures from PDB or theoretical models from ModBase. e23D allows visualization of the protein structure, modeling of recoding events and orientation of the editing with respect to nearby genomic functional sites from databases of disease causing mutations and genomic polymorphism. http://www.sheba-cancer.org.il/e23D CONTACT: oz.solomon@live.biu.ac.il or Eran.Eyal@sheba.health.gov.il.