The ENCODEdb portal: simplified access to ENCODE Consortium data

A Functional SNP in the Promoter of LBX1 Is Associated With the Development of Adolescent Idiopathic Scoliosis Through Involvement in the Myogenesis of Paraspinal Muscles

Previous studies have shown that LBX1 is associated with adolescent idiopathic scoliosis (AIS) in multiple populations. For the first time, rs1322330 located in the putative promoter region of LBX1 was found significantly associated with AIS in the Chinese population [p = 6.08 × 10^–14, odds ratio (OR) = 1.42, 95% confidence interval of 1.03–1.55]. Moreover, the luciferase assay and electrophoretic mobility shift assay supported that the allele A of rs1322330 could down-regulate the expression of LBX1 in the paraspinal muscles of AIS. In addition, silencing LBX1 in the myosatellite cells resulted in significantly inhibited cell viability and myotube formation, which supported an essential role of LBX1 in muscle development of AIS. To summarize, rs1322330 may be a novel functional SNP regulating the expression of LBX1, which was involved in the etiology of AIS possibly via regulation of myogenesis in the paraspinal muscles.

Genetic Variant of NFIB is Associated With the Metastasis of Osteosarcoma in Chinese Population

Variant rs7034162 in NFIB was reported to be associated with metastasis of osteosarcoma in European cases with genome-wide significance. Our purpose was to replicate the association of rs7034162 with the metastasis of osteosarcoma in the Chinese population and to further characterize the expression level of NFIB in osteosarcoma tissues. A total of 321 patients were included in this study. Variant rs7034162 was genotyped for each patient using the Taqman genotyping assay. Fifty-two cases of tumor tissues and adjacent normal tissues were collected during surgery. The χ² test was used to investigate the association of rs7034162 with the metastasis of osteosarcoma. The Student t test was used to compare the gene expression between patients with metastasis and those without metastasis. The messenger RNA expression level of NFIB was then compared among different genotypes of rs7034162 with 1-way analysis of variance test. Ninety-three patients were found to have metastasis. Patients with genotype AA had remarkably higher incidence of metastasis than those with genotype TT (34.4% vs 17.1%, P = .002). Patients with metastasis were found to have significantly higher rate of allele A than those without metastasis (53.2% vs 43.9%, P = .03). The messenger RNA expression of NFIB was significantly lower in tumor tissues of patients with metastasis than in those without metastasis (0.00035 ± 0.00017 vs 0.00063 ± 0.0025, P < .001). Compared to patients with genotype TT, those with genotype AA had remarkably decreased expression of NFIB (0.00033 ± 0.0014 vs 0.00067 ± 0.00037, P = .01). Single-nucleotide polymorphism rs7034162 was associated with metastasis of osteosarcoma in the Chinese population possibly via downregulation of NFIB. Further network analyses revealing the related pathways can help elucidate the molecular mechanism of distant metastasis in patients with osteosarcoma.

linc00673 (ERRLR01) is a prognostic indicator of overall survival in breast cancer

LncRNAs are novel noncoding RNAs involved in the epigenetic regulation of gene expression by recruiting ribonucleoprotein complexes to specific genomic loci to initiate histone methylation and/or other chromatin modifications. LncRNAs themselves function as tumor suppressors or oncogenes, depending on the gene regulatory networks they govern. We identified lnc00673 (ERRLR01) as a marker of overall survival (OS) in breast cancer patients. Specifically, ERRLR01 levels were elevated in triple-negative breast cancer (TNBC) as compared with Luminal-A, Luminal-B, and HER2 breast cancer subtypes. ERRLR01 levels were also inversely correlated with breast cancer survival across all breast cancer patients. Upon stratification, OS in ERα^- tumors correlated with negative overall survival, while in ERα⁺ tumors, ERRLR01 correlated with positive outcomes. This suggests ERRLR01 is modulated by hormone signaling in breast cancer. Gene-network analysis revealed ERRLR01 correlated with distinct pathways including "epithelial development" and "cellular differentiation." These data suggest ERRLR01 operates as an oncogene in TNBC, as well as a biomarker in breast cancer patients.

Identification and computational analysis of gene regulatory elements

Over the last two decades, advances in experimental and computational technologies have greatly facilitated genomic research. Next-generation sequencing technologies have made de novo sequencing of large genomes affordable, and powerful computational approaches have enabled accurate annotations of genomic DNA sequences. Charting functional regions in genomes must account for not only the coding sequences, but also noncoding RNAs, repetitive elements, chromatin states, epigenetic modifications, and gene regulatory elements. A mix of comparative genomics, high-throughput biological experiments, and machine learning approaches has played a major role in this truly global effort. Here we describe some of these approaches and provide an account of our current understanding of the complex landscape of the human genome. We also present overviews of different publicly available, large-scale experimental data sets and computational tools, which we hope will prove beneficial for researchers working with large and complex genomes.

ASPic-GeneID: a lightweight pipeline for gene prediction and alternative isoforms detection

New genomes are being sequenced at an increasingly rapid rate, far outpacing the rate at which manual gene annotation can be performed. Automated genome annotation is thus necessitated by this growth in genome projects; however, full-fledged annotation systems are usually home-grown and customized to a particular genome. There is thus a renewed need for accurate ab initio gene prediction methods. However, it is apparent that fully ab initio methods fall short of the required level of sensitivity and specificity for a quality annotation. Evidence in the form of expressed sequences gives the single biggest improvement in accuracy when used to inform gene predictions. Here, we present a lightweight pipeline for first-pass gene prediction on newly sequenced genomes. The two main components are ASPic, a program that derives highly accurate, albeit not necessarily complete, EST-based transcript annotations from EST alignments, and GeneID, a standard gene prediction program, which we have modified to take as evidence intron annotations. The introns output by ASPic CDS predictions is given to GeneID to constrain the exon-chaining process and produce predictions consistent with the underlying EST alignments. The pipeline was successfully tested on the entire C. elegans genome and the 44 ENCODE human pilot regions.

From cells to chromatin: capturing snapshots of genome organization with 5C technology

In eukaryotes, genome organization can be observed on many levels and at different scales. This organization is important not only to reduce chromosome length but also for the proper execution of various biological processes. High-resolution mapping of spatial chromatin structure was made possible by the development of the chromosome conformation capture (3C) technique. 3C uses chemical cross-linking followed by proximity-based ligation of fragmented DNA to capture frequently interacting chromatin segments in cell populations. Several 3C-related methods capable of higher chromosome conformation mapping throughput were reported afterwards. These techniques include the 3C-carbon copy (5C) approach, which offers the advantage of being highly quantitative and reproducible. We provide here an updated reference protocol for the production of 5C libraries analyzed by next-generation sequencing or onto microarrays. A procedure used to verify that 3C library templates bear the high quality required to produce superior 5C libraries is also described. We believe that this detailed protocol will help guide researchers in probing spatial genome organization and its role in various biological processes.

Sharing and archiving nucleic acid structure mapping data

Nucleic acids are particularly amenable to structural characterization using chemical and enzymatic probes. Each individual structure mapping experiment reveals specific information about the structure and/or dynamics of the nucleic acid. Currently, there is no simple approach for making these data publically available in a standardized format. We therefore developed a standard for reporting the results of single nucleotide resolution nucleic acid structure mapping experiments, or SNRNASMs. We propose a schema for sharing nucleic acid chemical probing data that uses generic public servers for storing, retrieving, and searching the data. We have also developed a consistent nomenclature (ontology) within the Ontology of Biomedical Investigations (OBI), which provides unique identifiers (termed persistent URLs, or PURLs) for classifying the data. Links to standardized data sets shared using our proposed format along with a tutorial and links to templates can be found at http://snrnasm.bio.unc.edu.

Disease-associated mutations that alter the RNA structural ensemble

Genome-wide association studies (GWAS) often identify disease-associated mutations in intergenic and non-coding regions of the genome. Given the high percentage of the human genome that is transcribed, we postulate that for some observed associations the disease phenotype is caused by a structural rearrangement in a regulatory region of the RNA transcript. To identify such mutations, we have performed a genome-wide analysis of all known disease-associated Single Nucleotide Polymorphisms (SNPs) from the Human Gene Mutation Database (HGMD) that map to the untranslated regions (UTRs) of a gene. Rather than using minimum free energy approaches (e.g. mFold), we use a partition function calculation that takes into consideration the ensemble of possible RNA conformations for a given sequence. We identified in the human genome disease-associated SNPs that significantly alter the global conformation of the UTR to which they map. For six disease-states (Hyperferritinemia Cataract Syndrome, β-Thalassemia, Cartilage-Hair Hypoplasia, Retinoblastoma, Chronic Obstructive Pulmonary Disease (COPD), and Hypertension), we identified multiple SNPs in UTRs that alter the mRNA structural ensemble of the associated genes. Using a Boltzmann sampling procedure for sub-optimal RNA structures, we are able to characterize and visualize the nature of the conformational changes induced by the disease-associated mutations in the structural ensemble. We observe in several cases (specifically the 5′ UTRs of FTL and RB1) SNP–induced conformational changes analogous to those observed in bacterial regulatory Riboswitches when specific ligands bind. We propose that the UTR and SNP combinations we identify constitute a “RiboSNitch,” that is a regulatory RNA in which a specific SNP has a structural consequence that results in a disease phenotype. Our SNPfold algorithm can help identify RiboSNitches by leveraging GWAS data and an analysis of the mRNA structural ensemble.

Genome-wide association studies identify mutations in the human genome that correlate with a particular disease. It is common to find mutations associated with disease in the non-coding region of the genome. These non-coding mutations are more difficult to interpret at a molecular level, because they do not affect the protein sequence. In this study, we analyze disease-associated mutations in non-coding regions of our genome in the context of their structural effect on the message of genetic information in our cells, Ribonucleic Acid (RNA). We focus in particular on the regulatory parts of our genes known as untranslated regions. We find that certain disease-associated mutations in these regulatory untranslated regions have a significant effect on the structure of the RNA message. We call these elements “RiboSNitches,” because they act like switches turning on and off genes, but are caused by Single Nucleotide Polymorphisms (SNPs), which are single point mutations in our genome. The RiboSNitches we identify are potentially a new class of pharmaceutical targets, as it is possible to change the structure of RNA with small drug-like molecules.

Genotype-phenotype databases: challenges and solutions for the post-genomic era

The flow of research data concerning the genetic basis of health and disease is rapidly increasing in speed and complexity. In response, many projects are seeking to ensure that there are appropriate informatics tools, systems and databases available to manage and exploit this flood of information. Previous solutions, such as central databases, journal-based publication and manually intensive data curation, are now being enhanced with new systems for federated databases, database publication, and more automated management of data flows and quality control. Along with emerging technologies that enhance connectivity and data retrieval, these advances should help to create a powerful knowledge environment for genotype-phenotype information.

WebScipio: an online tool for the determination of gene structures using protein sequences

Background

Obtaining the gene structure for a given protein encoding gene is an important step in many analyses. A software suited for this task should be readily accessible, accurate, easy to handle and should provide the user with a coherent representation of the most probable gene structure. It should be rigorous enough to optimise features on the level of single bases and at the same time flexible enough to allow for cross-species searches.

Results

WebScipio, a web interface to the Scipio software, allows a user to obtain the corresponding coding sequence structure of a here given a query protein sequence that belongs to an already assembled eukaryotic genome. The resulting gene structure is presented in various human readable formats like a schematic representation, and a detailed alignment of the query and the target sequence highlighting any discrepancies. WebScipio can also be used to identify and characterise the gene structures of homologs in related organisms. In addition, it offers a web service for integration with other programs.

Conclusion

WebScipio is a tool that allows users to get a high-quality gene structure prediction from a protein query. It offers more than 250 eukaryotic genomes that can be searched and produces predictions that are close to what can be achieved by manual annotation, for in-species and cross-species searches alike. WebScipio is freely accessible at .

High-throughput single-nucleotide structural mapping by capillary automated footprinting analysis

The use of capillary electrophoresis with fluorescently labeled nucleic acids revolutionized DNA sequencing, effectively fueling the genomic revolution. We present an application of this technology for the high-throughput structural analysis of nucleic acids by chemical and enzymatic mapping (‘footprinting’). We achieve the throughput and data quality necessary for genomic-scale structural analysis by combining fluorophore labeling of nucleic acids with novel quantitation algorithms. We implemented these algorithms in the CAFA (capillary automated footprinting analysis) open-source software that is downloadable gratis from https://simtk.org/home/cafa. The accuracy, throughput and reproducibility of CAFA analysis are demonstrated using hydroxyl radical footprinting of RNA. The versatility of CAFA is illustrated by dimethyl sulfate mapping of RNA secondary structure and DNase I mapping of a protein binding to a specific sequence of DNA. Our experimental and computational approach facilitates the acquisition of high-throughput chemical probing data for solution structural analysis of nucleic acids.