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Development of SNPs markers from pooled Rad-seq data and high-throughput genotyping, applied to the study of several harvested population genetics in the Upper-Maroni (French guiana). 17. Journées Ouvertes de Biologie, Informatique et Mathématiques

Mammalian genomes encode numerous natural antisense long noncoding RNAs (lncRNAs) that regulate gene expression. Recently, an antisense lncRNA to mouse Ubiquitin carboxyl-terminal hydrolase L1 (Uchl1) was reported to increase UCHL1 protein synthesis, representing a new functional class of lncRNAs, designated as SINEUPs, for SINE element-containing translation UP-regulators. Here, we show that an antisense lncRNA to the human protein phosphatase 1 regulatory subunit 12A (PPP1R12A), named as R12A-AS1, which overlaps with the 5′ UTR and first coding exon of the PPP1R12A mRNA, functions as a SINEUP, increasing PPP1R12A protein translation in human cells. The SINEUP activity depends on the aforementioned sense-antisense interaction and a free right Alu monomer repeat element at the 3′ end of R12A-AS1. In addition, we identify another human antisense lncRNA with SINEUP activity. Our results demonstrate for the first time that human natural antisense lncRNAs can up-regulate protein translation, suggesting that endogenous SINEUPs may be widespread and present in many mammalian species.

International audience; Internal bases in mRNA can be subjected to modifications that influence the fate of mRNA in cells. One of the most prevalent modified bases is found at the 5' end of mRNA, at the first encoded nucleotide adjacent to the 7-methylguanosine cap. Here we show that this nucleotide, N-6,2'-O-dimethyladenosine (m(6)A(m)), is a reversible modification that influences cellular mRNA fate. Using a transcriptome-wide map of m(6)A(m) we find that m(6)A(m)-initiated transcripts are markedly more stable than mRNAs that begin with other nucleotides. We show that the enhanced stability of m(6)A(m)-initiated transcripts is due to resistance to the mRNA-decapping enzyme DCP2. Moreover, we find that m(6)A(m) is selectively demethylated by fat mass and obesity-associated protein (FTO). FTO preferentially demethylates m(6)A(m) rather than N-6-methyladenosine (m(6)A), and reduces the stability of m(6)A(m) mRNAs. Together, these findings show that the methylation status of m(6)A(m) in the 5' cap is a dynamic and reversible epitranscriptomic modification that determines mRNA stability.

Zebrafish (Danio rerio) has emerged as a model organism to investigate vertebrate development and human genetic diseases. However, the zebrafish genome annotation is still ongoing and incomplete, and there are still new gene transcripts to be found. With the introduction of massive parallel sequencing, whole transcriptome studies became possible. In the present study, we aimed to discover novel transcribed regions (NTRs) using developmental transcriptome data from RNA sequencing. In order to achieve this, we developed an in-house bioinformatics pipeline for NTR discovery. Using the pipeline, we detected 152 putative NTRs that at the time of discovery were not annotated in Ensembl and NCBI gene database. Four randomly selected NTRs were successfully validated using RT-PCR, and expression profiles of 10 randomly selected NTRs were evaluated using qRT-PCR. The identification of these 152 NTRs provide new information for zebrafish genome annotation as well as new candidates for studies of zebrafish gene function.

Comprehensive genome-wide DNA methylation studies in neuroblastoma (NB), a childhood tumor that originates from precursor cells of the sympathetic nervous system, are scarce. Recently, we profiled the DNA methylome of 102 well-annotated primary NB tumors by methyl-CpG-binding domain (MBD) sequencing, in order to identify prognostic biomarker candidates. In this data descriptor, we give details on how this data set was generated and which bioinformatics analyses were applied during data processing. Through a series of technical validations, we illustrate that the data are of high quality and that the sequenced fragments represent methylated genomic regions. Furthermore, genes previously described to be methylated in NB are confirmed. As such, these MBD sequencing data are a valuable resource to further study the association of NB risk factors with the NB methylome, and offer the opportunity to integrate methylome data with other -omic data sets on the same tumor samples such as gene copy number and gene expression, also publically available.

The transcriptome analysis of whole-blood RNA by sequencing holds promise for the identification and tracking of biomarkers; however, the high globin mRNA (gmRNA) content of erythrocytes hampers whole-blood and buffy coat analyses. We introduce a novel gmRNA locking assay (GlobinLock, GL) as a robust and simple gmRNA reduction tool to preserve RNA quality, save time and cost. GL consists of a pair of gmRNA-specific oligonucleotides in RNA initial denaturation buffer that is effective immediately after RNA denaturation and adds only ten minutes of incubation to the whole cDNA synthesis procedure when compared to non-blood RNA analysis. We show that GL is fully effective not only for human samples but also for mouse and rat and so far incompletely studied cow, dog and zebrafish.

We characterized the epigenetic landscape of genes encoding long noncoding RNAs (lncRNAs) across 6,475 tumors and 455 cancer cell lines. In stark contrast to the CpG island hypermethylation phenotype in cancer, we observed a recurrent hypomethylation of 1,006 lncRNA genes in cancer, including EPIC1 (epigenetically-induced lncRNA1). Overexpression of EPIC1 is associated with poor prognosis in luminal B breast cancer patients and enhances tumor growth in vitro and in vivo. Mechanistically, EPIC1 promotes cell-cycle progression by interacting with MYC through EPIC1's 129–283 nt region. EPIC1 knockdown reduces the occupancy of MYC to its target genes (e.g., CDKN1A, CCNA2, CDC20, and CDC45). MYC depletion abolishes EPIC1's regulation of MYC target and luminal breast cancer tumorigenesis in vitro and in vivo. Wang et al. characterize the epigenetic landscape of lncRNAs genes across a large number of human tumors and cancer cell lines and observe recurrent hypomethylation of lncRNA genes, including EPIC1. EPIC1 RNA promotes cell-cycle progression by interacting with MYC and enhancing its binding to target genes.

Parametric polymorphism constrains the behavior of pure functional programs in a way that allows the derivation of interesting theorems about them solely from their types, i.e., virtually for free. The formal background of such 'free theorems' is well developed for extensions of the Girard-Reynolds polymorphic lambda calculus by algebraic datatypes and general recursion, provided the resulting calculus is endowed with either a purely strict or a purely nonstrict semantics. But modern functional languages like Clean and Haskell, while using nonstrict evaluation by default, also provide means to enforce strict evaluation of subcomputations at will. The resulting selective strictness gives the advanced programmer explicit control over evaluation order, but is not without semantic consequences: it breaks standard parametricity results. This paper develops an operational semantics for a core calculus supporting all the language features emphasized above. Its main achievement is the characterization of observational approximation with respect to this operational semantics via a carefully constructed logical relation. This establishes the formal basis for new parametricity results, as illustrated by several example applications, including the first complete correctness proof for short cut fusion in the presence of selective strictness. The focus on observational approximation, rather than equivalence, allows a finer-grained analysis of computational behavior in the presence of selective strictness than would be possible with observational equivalence alone. © 2007 Elsevier Ltd. All rights reserved.

Pre-eclampsia is a common and complex pregnancy disorder that often involves impaired placental development. In order to identify altered gene expression in pre-eclamptic placenta, we sequenced placental transcriptomes of nine pre-eclamptic and nine healthy pregnant women in pools of three. The differential gene expression was tested both by including all the pools in the analysis and by excluding some of the pools based on phenotypic characteristics. From these analyses, we identified altogether 53 differently expressed genes, a subset of which was validated by qPCR in 20 cases and 19 controls. Furthermore, we conducted pathway and functional analyses which revealed disturbed vascular function and immunological balance in pre-eclamptic placenta. Some of the genes identified in our study have been reported by numerous microarray studies (BHLHE40, FSTL3, HK2, HTRA4, LEP, PVRL4, SASH1, SIGLEC6), but many have been implicated in only few studies or have not previously been linked to pre-eclampsia (ARMS2, BTNL9, CCSAP, DIO2, FER1L4, HPSE, LOC100129345, LYN, MYO7B, NCMAP, NDRG1, NRIP1, PLIN2, SBSPON, SERPINB9, SH3BP5, TET3, TPBG, ZNF175). Several of the molecules produced by these genes may have a role in the pathogenesis of pre-eclampsia and some could qualify as biomarkers for prediction or detection of this pregnancy complication.

Background Burkholderia cenocepacia is a soil-dwelling Gram-negative Betaproteobacterium with an important role as opportunistic pathogen in humans. Infections with B. cenocepacia are very difficult to treat due to their high intrinsic resistance to most antibiotics. Biofilm formation further adds to their antibiotic resistance. B. cenocepacia harbours a large, multi-replicon genome with a high GC-content, the reference genome of strain J2315 includes 7374 annotated genes. This study aims to annotate transcription start sites and identify novel transcripts on a whole genome scale. Methods RNA extracted from B. cenocepacia J2315 biofilms was analysed by differential RNA-sequencing and the resulting dataset compared to data derived from conventional, global RNA-sequencing. Transcription start sites were annotated and further analysed according to their position relative to annotated genes. Results Four thousand ten transcription start sites were mapped over the whole B. cenocepacia genome and the primary transcription start site of 2089 genes expressed in B. cenocepacia biofilms were defined. For 64 genes a start codon alternative to the annotated one was proposed. Substantial antisense transcription for 105 genes and two novel protein coding sequences were identified. The distribution of internal transcription start sites can be used to identify genomic islands in B. cenocepacia. A potassium pump strongly induced only under biofilm conditions was found and 15 non-coding small RNAs highly expressed in biofilms were discovered. Conclusions Mapping transcription start sites across the B. cenocepacia genome added relevant information to the J2315 annotation. Genes and novel regulatory RNAs putatively involved in B. cenocepacia biofilm formation were identified. These findings will help in understanding regulation of B. cenocepacia biofilm formation. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1993-3) contains supplementary material, which is available to authorized users.

Background RNA-sequencing (RNA-seq) is a powerful technique for the identification of genetic variants that affect gene-expression levels, either through expression quantitative trait locus (eQTL) mapping or through allele-specific expression (ASE) analysis. Given increasing numbers of RNA-seq samples in the public domain, we here studied to what extent eQTLs and ASE effects can be identified when using public RNA-seq data while deriving the genotypes from the RNA-sequencing reads themselves. Methods We downloaded the raw reads for all available human RNA-seq datasets. Using these reads we performed gene expression quantification. All samples were jointly normalized and subjected to a strict quality control. We also derived genotypes using the RNA-seq reads and used imputation to infer non-coding variants. This allowed us to perform eQTL mapping and ASE analyses jointly on all samples that passed quality control. Our results were validated using samples for which DNA-seq genotypes were available. Results 4,978 public human RNA-seq runs, representing many different tissues and cell-types, passed quality control. Even though these data originated from many different laboratories, samples reflecting the same cell type clustered together, suggesting that technical biases due to different sequencing protocols are limited. In a joint analysis on the 1,262 samples with high quality genotypes, we identified cis-eQTLs effects for 8,034 unique genes (at a false discovery rate ≤0.05). eQTL mapping on individual tissues revealed that a limited number of samples already suffice to identify tissue-specific eQTLs for known disease-associated genetic variants. Additionally, we observed strong ASE effects for 34 rare pathogenic variants, corroborating previously observed effects on the corresponding protein levels. Conclusions By deriving and imputing genotypes from RNA-seq data, it is possible to identify both eQTLs and ASE effects. Given the exponential growth of the number of publicly available RNA-seq samples, we expect this approach will become especially relevant for studying the effects of tissue-specific and rare pathogenic genetic variants to aid clinical interpretation of exome and genome sequencing. Electronic supplementary material The online version of this article (doi:10.1186/s13073-015-0152-4) contains supplementary material, which is available to authorized users.

This study presents a dynamic characterization of the sheep milk transcriptome aiming at achieving a better understanding of the sheep lactating mammary gland. Transcriptome sequencing (RNA-seq) was performed on total RNA extracted from milk somatic cells from ewes on days 10, 50, 120 and 150 after lambing. The experiment was performed in Spanish Churra and Assaf breeds, which differ in their milk production traits. Nearly 67% of the annotated genes in the reference genome (Oar_v3.1) were expressed in ovine milk somatic cells. For the two breeds and across the four lactation stages studied, the most highly expressed genes encoded caseins and whey proteins. We detected 573 differentially expressed genes (DEGs) across lactation points, with the largest differences being found, between day 10 and day 150. Upregulated GO terms at late lactation stages were linked mainly to developmental processes linked to extracellular matrix remodeling. A total of 256 annotated DEGs were detected in the Assaf and Churra comparison. Some genes selectively upregulated in the Churra breed grouped under the endopeptidase and channel activity GO terms. These genes could be related to the higher cheese yield of this breed. Overall, this study provides the first integrated overview on sheep milk gene expression.

RNA sequencing has become widely used in gene expression profiling experiments. Prior to any RNA sequencing experiment the quality of the RNA must be measured to assess whether or not it can be used for further downstream analysis. The RNA integrity number (RIN) is a scale used to measure the quality of RNA that runs from 1 (completely degraded) to 10 (intact). Ideally, samples with high RIN (>8) are used in RNA sequencing experiments. RNA, however, is a fragile molecule which is susceptible to degradation and obtaining high quality RNA is often hard, or even impossible when extracting RNA from certain clinical tissues. Thus, occasionally, working with low quality RNA is the only option the researcher has. Here we investigate the effects of RIN on RNA sequencing and suggest a computational method to handle data from samples with low quality RNA which also enables reanalysis of published datasets. Using RNA from a human cell line we generated and sequenced samples with varying RINs and illustrate what effect the RIN has on the basic procedure of RNA sequencing; both quality aspects and differential expression. We show that the RIN has systematic effects on gene coverage, false positives in differential expression and the quantification of duplicate reads. We introduce 3' tag counting (3TC) as a computational approach to reliably estimate differential expression for samples with low RIN. We show that using the 3TC method in differential expression analysis significantly reduces false positives when comparing samples with different RIN, while retaining reasonable sensitivity. QC 20140423

Integrative ChIP-seq/Microarray Analysis Identifies a CTNNB1 Target Signature Enriched in Intestinal Stem Cells and Colon Cancer Kazuhide Watanabe 1 , Jacob Biesinger 2,3 , Michael L. Salmans 1 , Brian S. Roberts 4 , William T. Arthur 4 , Michele Cleary 4 , Bogi Andersen 1 , Xiaohui Xie 2,3 , Xing Dai 1,2 * 1 Department of Biological Chemistry, School of Medicine, University of California Irvine, Irvine, California, United States of America, 2 Institute for Genomics and Bioinformatics, University of California Irvine, Irvine, California, United States of America, 3 Department of Computer Science, University of California Irvine, Irvine, California, United States of America, 4 Rosetta Inpharmatics, LLC, Merck & Co Inc., Seattle, Washington, United States of America Abstract Background: Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. Results: We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5 + intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Conclusion: Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells. Citation: Watanabe K, Biesinger J, Salmans ML, Roberts BS, Arthur WT, et al. (2014) Integrative ChIP-seq/Microarray Analysis Identifies a CTNNB1 Target Signature Enriched in Intestinal Stem Cells and Colon Cancer. PLoS ONE 9(3): e92317. doi:10.1371/journal.pone.0092317 Editor: Ted S. Acott, Casey Eye Institute, United States of America Received October 30, 2013; Accepted February 20, 2014; Published March 20, 2014 Copyright: s 2014 Watanabe et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: Funding from Susan G. Komen grant KG110897 (XD), a U.S. Department of Defense BCRP Postdoctoral Fellowship (K.W. W81XWH-10-1-0383), and National Institutes of Health grant R01HG006870 (to XX). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: Brian S. Roberts and William T. Arthur are former employees of Rosetta Inpharmatics, LLC, Merck & Co Inc. Michele Cleary is currently an employee of Merck & Co., Inc. There are no patents, products in development or marketed products to declare. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors. * E-mail: xdai@uci.edu leads to abnormal proliferation of mutated cells through activation of target genes such as MYC and CCND1 [7]. However, given the divergent cellular roles of Wnt/CTNNB1 signaling, other target genes may also contribute to the pathogenesis of CRCs. Thus, identification and characterization of CTNNB1 target genes genome-wide have been an important pursuit in CRC studies. Transcriptional profiling was used to identify Wnt/ CTNNB1 target genes in colon cancer cells [8]. However, analysis of gene expression alone is limited due to inability to distinguish between primary and secondary effects of Wnt pathway activation. More recently, chromatin immunoprecipitation (ChIP) followed by large-scale DNA analysis such as DNA-chip (ChIP-chip) or high-throughput sequencing (ChIP-seq) [9,10] was used to identify the genomic loci to which CTNNB1 or TCF factors directly bind [11–14]. However, ChIP-based studies of various transcription factors suggest that not all binding events identified correlate with Background Wnt/CTNNB1 signaling is a conserved pathway that plays fundamental roles in embryonic development, tissue homeostasis and maintenance of stem cells. In normal intestine, this pathway is essential for the development and maintenance of intestinal stem cells [1,2]. Activation of canonical Wnt signaling involves stabilization of cytoplasmic CTNNB1, which is otherwise degrad- ed by the proteasome through a degradation complex composed of tumor suppressor protein APC, serine/threonine kinase GSK-3, and Axin. Stabilized CTNNB1 translocates into the nucleus where it binds to TCF/LEF transcription factors and activates target gene expression [2]. A key initiation event of colorectal cancers (CRCs) is CTNNB1 stabilization through loss of the APC gene or activating mutations in the CTNNB1 gene [3]. This genetic event occurs primarily in the intestinal stem cell population [4–6] and PLOS ONE | www.plosone.org March 2014 | Volume 9 | Issue 3 | e92317

Background Next generation sequencing (NGS) technologies can be applied in complex microbial ecosystems for metatranscriptome analysis by employing direct cDNA sequencing, which is known as RNA sequencing (RNA-seq). RNA-seq generates large datasets of great complexity, the comprehensive interpretation of which requires a reliable bioinformatic pipeline. In this study, we focus on the development of such a metatranscriptome pipeline, which we validate using Illumina RNA-seq datasets derived from the small intestine microbiota of two individuals with an ileostomy. Results The metatranscriptome pipeline developed here enabled effective removal of rRNA derived sequences, followed by confident assignment of the predicted function and taxonomic origin of the mRNA reads. Phylogenetic analysis of the small intestine metatranscriptome datasets revealed a strong similarity with the community composition profiles obtained from 16S rDNA and rRNA pyrosequencing, indicating considerable congruency between community composition (rDNA), and the taxonomic distribution of overall (rRNA) and specific (mRNA) activity among its microbial members. Reproducibility of the metatranscriptome sequencing approach was established by independent duplicate experiments. In addition, comparison of metatranscriptome analysis employing single- or paired-end sequencing methods indicated that the latter approach does not provide improved functional or phylogenetic insights. Metatranscriptome functional-mapping allowed the analysis of global, and genus specific activity of the microbiota, and illustrated the potential of these approaches to unravel syntrophic interactions in microbial ecosystems. Conclusions A reliable pipeline for metatransciptome data analysis was developed and evaluated using RNA-seq datasets obtained for the human small intestine microbiota. The set-up of the pipeline is very generic and can be applied for (bacterial) metatranscriptome analysis in any chosen niche.

Recent statistical analyses suggest that sequencing of pooled samples provides a cost effective approach to determine genome-wide population genetic parameters. Here we introduce PoPoolation, a toolbox specifically designed for the population genetic analysis of sequence data from pooled individuals. PoPoolation calculates estimates of θWatterson, θπ, and Tajima's D that account for the bias introduced by pooling and sequencing errors, as well as divergence between species. Results of genome-wide analyses can be graphically displayed in a sliding window plot. PoPoolation is written in Perl and R and it builds on commonly used data formats. Its source code can be downloaded from http://code.google.com/p/popoolation/. Furthermore, we evaluate the influence of mapping algorithms, sequencing errors, and read coverage on the accuracy of population genetic parameter estimates from pooled data.

Stage de DEA. Rapport de stage.; Ce rapport se concentre sur l'étude d'une solution algorithmique liée au problème du consensus, à savoir sa complexité, ses propriétés temporelles et sa validation en environnement simulé. En effet, lors d'un précédent projet du nom d'ATR (Accord Temps Réel ), la société AXLOG Ingénierie, en collaboration avec des laboratoires de recherche, s'est penchée sur la validation d'un algorithme de diffusion atomique. Les résultats de cette dernière étant forts encourageants, AXLOG décida de poursuivre son effort sur un autre problème d'algorithmique distribuée, le consensus, en collaboration avec M. Gérard Le Lann de l'INRIA. Il s'agira pour nous de proposer les solutions " les meilleures " à des problèmes ayant des contraintes différentes (en coûts, performance, sûreté de fonctionnement). Ainsi pour une première implantation qui aura pour cible des satellites, nous étudierons une solution essentiellement " hardware " afin de garantir de meilleures performances. || This report focuses on the latest consensus algorithm, its complexity, its temporal properties, and its validation under an simulated environment. Indeed, in a former project named ATR, AXLOG Ingénierie, associated with some research laboratories, deals w