Identification of agonists for a group of human odorant receptors

Olfaction plays a critical role in several aspects of the human life. Odorants are detected by hundreds of odorant receptors (ORs) which belong to the superfamily of G protein-coupled receptors. These receptors are expressed in the olfactory sensory neurons of the nose. The information provided by the activation of different combinations of ORs in the nose is transmitted to the brain, leading to odorant perception and emotional and behavioral responses. There are ~400 intact human ORs, and to date only a small percentage of these receptors (~10%) have known agonists. The determination of the specificity of the human ORs will contribute to a better understanding of how odorants are discriminated by the olfactory system. In this work, we aimed to identify human specific ORs, that is, ORs that are present in humans but absent from other species, and their corresponding agonists. To do this, we first selected 22 OR gene sequences from the human genome with no counterparts in the mouse, rat or dog genomes. Then we used a heterologous expression system to screen a subset of these human ORs against a panel of odorants of biological relevance, including foodborne aroma volatiles. We found that different types of odorants are able to activate some of these previously uncharacterized human ORs

miRIAD-integrating microRNA inter- and intragenic data

MicroRNAs (miRNAs) are a class of small (similar to 22 nucleotides) non-coding RNAs that post-transcriptionally regulate gene expression by interacting with target mRNAs. A majority of miRNAs is located within intronic or exonic regions of protein-coding genes (host genes), and increasing evidence suggests a functional relationship between these miRNAs and their host genes. Here, we introduce miRIAD, a web-service to facilitate the analysis of genomic and structural features of intragenic miRNAs and their host genes for five species (human, rhesus monkey, mouse, chicken and opossum). miRIAD contains the genomic classification of all miRNAs (inter-and intragenic), as well as classification of all protein-coding genes into host or non-host genes (depending on whether they contain an intragenic miRNA or not). We collected and processed public data from several sources to provide a clear visualization of relevant knowledge related to intragenic miRNAs, such as host gene function, genomic context, names of and references to intragenic miRNAs, miRNA binding sites, clusters of intragenic miRNAs, miRNA and host gene expression across different tissues and expression correlation for intragenic miRNAs and their host genes. Protein-protein interaction data are also presented for functional network analysis of host genes. In summary, miRIAD was designed to help the research community to explore, in a user-friendly environment, intragenic miRNAs, their host genes and functional annotations with minimal effort, facilitating hypothesis generation and in-silico validations

miRIAD-integrating microRNA inter- and intragenic data

MicroRNAs (miRNAs) are a class of small (similar to 22 nucleotides) non-coding RNAs that post-transcriptionally regulate gene expression by interacting with target mRNAs. A majority of miRNAs is located within intronic or exonic regions of protein-coding genes (host genes), and increasing evidence suggests a functional relationship between these miRNAs and their host genes. Here, we introduce miRIAD, a web-service to facilitate the analysis of genomic and structural features of intragenic miRNAs and their host genes for five species (human, rhesus monkey, mouse, chicken and opossum). miRIAD contains the genomic classification of all miRNAs (inter-and intragenic), as well as classification of all protein-coding genes into host or non-host genes (depending on whether they contain an intragenic miRNA or not). We collected and processed public data from several sources to provide a clear visualization of relevant knowledge related to intragenic miRNAs, such as host gene function, genomic context, names of and references to intragenic miRNAs, miRNA binding sites, clusters of intragenic miRNAs, miRNA and host gene expression across different tissues and expression correlation for intragenic miRNAs and their host genes. Protein-protein interaction data are also presented for functional network analysis of host genes. In summary, miRIAD was designed to help the research community to explore, in a user-friendly environment, intragenic miRNAs, their host genes and functional annotations with minimal effort, facilitating hypothesis generation and in-silico validations

MiRIAD update: using alternative polyadenylation, protein interaction network analysis and additional species to enhance exploration of the role of intragenic miRNAs and their host genes

MicroRNAs have established their role as potent regulators of the epigenome. Interestingly, most miRNAs are located within protein-coding genes with functional consequences that have yet to be fully investigated. MiRIAD is a database with an interactive and user-friendly online interface that has been facilitating research on intragenic miRNAs. In this article, we present a major update. First, data for five additional species (chimpanzee, rat, dog, cow and frog) were added to support the exploration of evolutionary aspects of the relationship between host genes and intragenic miRNAs. Moreover, we integrated data from two different sources to generate a comprehensive alternative polyadenylation dataset. The miRIAD interface was therefore redesigned and provides a completely new gene model representation, including an interactive visualization of the 30 untranslated region (UTR) with alternative polyadenylation sites, corresponding signals and potential miRNA binding sites. Furthermore, we expanded on functional host gene network analysis. Although the previous version solely reported protein interactions, the update features a separate network analysis view that can either be accessed through the submission of a list of genes of interest or directly from a gene's list of protein interactions. In addition to statistical properties of the submitted gene set, the interaction network graph is presented and miRNAs with seed site over- and underrepresentation are identified. In summary, the update of miRIAD provides novel datasets and bioinformatics resources with a significant increase in functionality to facilitate intragenic miRNA research in a user-friendly and interactive way

Systematic detection of putative tumor suppressor genes through the combined use of exome and transcriptome sequencing

Abstract Background To identify potential tumor suppressor genes, genome-wide data from exome and transcriptome sequencing were combined to search for genes with loss of heterozygosity and allele-specific expression. The analysis was conducted on the breast cancer cell line HCC1954, and a lymphoblast cell line from the same individual, HCC1954BL. Results By comparing exome sequences from the two cell lines, we identified loss of heterozygosity events at 403 genes in HCC1954 and at one gene in HCC1954BL. The combination of exome and transcriptome sequence data also revealed 86 and 50 genes with allele specific expression events in HCC1954 and HCC1954BL, which comprise 5.4% and 2.6% of genes surveyed, respectively. Many of these genes identified by loss of heterozygosity and allele-specific expression are known or putative tumor suppressor genes, such as BRCA1, MSH3 and SETX, which participate in DNA repair pathways. Conclusions Our results demonstrate that the combined application of high throughput sequencing to exome and allele-specific transcriptome analysis can reveal genes with known tumor suppressor characteristics, and a shortlist of novel candidates for the study of tumor suppressor activities

Distinct patterns of somatic alterations in a lymphoblastoid and a tumor genome derived from the same individual

Although patterns of somatic alterations have been reported for tumor genomes, little is known on how they compare with alterations present in non-tumor genomes. A comparison of the two would be crucial to better characterize the genetic alterations driving tumorigenesis. We sequenced the genomes of a lymphoblastoid (HCC1954BL) and a breast tumor (HCC1954) cell line derived from the same patient and compared the somatic alterations present in both. The lymphoblastoid genome presents a comparable number and similar spectrum of nucleotide substitutions to that found in the tumor genome. However, a significant difference in the ratio of non-synonymous to synonymous substitutions was observed between both genomes (P = 0.031). Protein–protein interaction analysis revealed that mutations in the tumor genome preferentially affect hub-genes (P = 0.0017) and are co-selected to present synergistic functions (P < 0.0001). KEGG analysis showed that in the tumor genome most mutated genes were organized into signaling pathways related to tumorigenesis. No such organization or synergy was observed in the lymphoblastoid genome. Our results indicate that endogenous mutagens and replication errors can generate the overall number of mutations required to drive tumorigenesis and that it is the combination rather than the frequency of mutations that is crucial to complete tumorigenic transformation

Distinct patterns of somatic alterations in a lymphoblastoid and a tumor genome derived from the same individual

Although patterns of somatic alterations have been reported for tumor genomes, little is known on how they compare with alterations present in non-tumor genomes. A comparison of the two would be crucial to better characterize the genetic alterations driving tumorigenesis. We sequenced the genomes of a lymphoblastoid (HCC1954BL) and a breast tumor (HCC1954) cell line derived from the same patient and compared the somatic alterations present in both. The lymphoblastoid genome presents a comparable number and similar spectrum of nucleotide substitutions to that found in the tumor genome. However, a significant difference in the ratio of non-synonymous to synonymous substitutions was observed between both genomes (P = 0.031). Protein–protein interaction analysis revealed that mutations in the tumor genome preferentially affect hub-genes (P = 0.0017) and are co-selected to present synergistic functions (P < 0.0001). KEGG analysis showed that in the tumor genome most mutated genes were organized into signaling pathways related to tumorigenesis. No such organization or synergy was observed in the lymphoblastoid genome. Our results indicate that endogenous mutagens and replication errors can generate the overall number of mutations required to drive tumorigenesis and that it is the combination rather than the frequency of mutations that is crucial to complete tumorigenic transformation

Alternative splicing enriched cDNA libraries identify breast cancer-associated transcripts

<p>Abstract</p> <p>Background</p> <p>Alternative splicing (AS) is a central mechanism in the generation of genomic complexity and is a major contributor to transcriptome and proteome diversity. Alterations of the splicing process can lead to deregulation of crucial cellular processes and have been associated with a large spectrum of human diseases. Cancer-associated transcripts are potential molecular markers and may contribute to the development of more accurate diagnostic and prognostic methods and also serve as therapeutic targets. Alternative splicing-enriched cDNA libraries have been used to explore the variability generated by alternative splicing. In this study, by combining the use of trapping heteroduplexes and RNA amplification, we developed a powerful approach that enables transcriptome-wide exploration of the AS repertoire for identifying AS variants associated with breast tumor cells modulated by <it>ERBB2</it> (<it>HER-2/neu</it>) oncogene expression.</p> <p>Results</p> <p>The human breast cell line (C5.2) and a pool of 5 ERBB2 over-expressing breast tumor samples were used independently for the construction of two AS-enriched libraries. In total, 2,048 partial cDNA sequences were obtained, revealing 214 alternative splicing sequence-enriched tags (ASSETs). A subset with 79 multiple exon ASSETs was compared to public databases and reported 138 different AS events. A high success rate of RT-PCR validation (94.5%) was obtained, and 2 novel AS events were identified. The influence of <it>ERBB2</it>-mediated expression on AS regulation was evaluated by capillary electrophoresis and probe-ligation approaches in two mammary cell lines (Hb4a and C5.2) expressing different levels of <it>ERBB2</it>. The relative expression balance between AS variants from 3 genes was differentially modulated by <it>ERBB2</it> in this model system.</p> <p>Conclusions</p> <p>In this study, we presented a method for exploring AS from any RNA source in a transcriptome-wide format, which can be directly easily adapted to next generation sequencers. We identified AS transcripts that were differently modulated by <it>ERBB2</it>-mediated expression and that can be tested as molecular markers for breast cancer. Such a methodology will be useful for completely deciphering the cancer cell transcriptome diversity resulting from AS and for finding more precise molecular markers.</p

Common Promoter Elements in Odorant and Vomeronasal Receptor Genes

In mammals, odorants and pheromones are detected by hundreds of odorant receptors (ORs) and vomeronasal receptors (V1Rs and V2Rs) expressed by sensory neurons that are respectively located in the main olfactory epithelium and in the vomeronasal organ. Even though these two olfactory systems are functionally and anatomically separate, their sensory neurons show a common mechanism of receptor gene regulation: each neuron expresses a single receptor gene from a single allele. The mechanisms underlying OR and VR gene expression remain unclear. Here we investigated if OR and V1R genes share common sequences in their promoter regions