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Coronaviruses infect a wide variety of host species, resulting in a range of diseases in both humans and animals. The coronavirus genome consists of a large positive-sense single-stranded molecule of RNA containing many RNA structures. One structure, denoted s2m and consisting of 41 nucleotides, is located within the 3′ untranslated region (3′ UTR) and is shared between some coronavirus species, including infectious bronchitis virus (IBV), severe acute respiratory syndrome coronavirus (SARS-CoV), and SARS-CoV-2, as well as other pathogens, including human astrovirus. Using a reverse genetic system to generate recombinant viruses, we investigated the requirement of the s2m structure in the replication of IBV, a globally distributed economically important Gammacoronavirus that infects poultry causing respiratory disease. Deletion of three nucleotides predicted to destabilize the canonical structure of the s2m or the deletion of the nucleotides corresponding to s2m impacted viral replication in vitro. In vitro passaging of the recombinant IBV with the s2m sequence deleted resulted in a 36-nucleotide insertion in place of the deletion, which was identified to be composed of a duplication of flanking sequences. A similar result was observed following serial passage of human astrovirus with a deleted s2m sequence. RNA modeling indicated that deletion of the nucleotides corresponding to the s2m impacted other RNA structures present in the IBV 3′ UTR. Our results indicated for both IBV and human astrovirus a preference for nucleotide occupation in the genome location corresponding to the s2m, which is independent of the specific s2m sequence.

Androgen receptor (AR) plays a central role in driving prostate cancer (PCa) progression. How AR promotes this process is still not completely clear. Herein, we used single-cell transcriptome analysis to reconstruct the transcriptional network of AR in PCa. Our work shows AR directly regulates a set of signature genes in the ER-to-Golgi protein vesicle-mediated transport pathway. The expression of these genes is required for maximum androgen-dependent ER-to-Golgi trafficking, cell growth, and survival. Our analyses also reveal the signature genes are associated with PCa progression and prognosis. Moreover, we find inhibition of the ER-to-Golgi transport process with a small molecule enhanced antiandrogen-mediated tumor suppression of hormone-sensitive and insensitive PCa. Finally, we demonstrate AR collaborates with CREB3L2 in mediating ER-to-Golgi trafficking in PCa. In summary, our findings uncover a critical role for dysregulation of ER-to-Golgi trafficking expression and function in PCa progression, provide detailed mechanistic insights for how AR tightly controls this process, and highlight the prospect of targeting the ER-to-Golgi pathway as a therapeutic strategy for advanced PCa.

Funding: This work was supported by Biotechnology and Biological Sciences Research Council (BBSRC) grants BB/L003988/1 and 1645891, and strategic funding to The Pirbright Institute, BBS/E/I/00007035, BBS/E/I/00007034, BBS/E/I/00007037 and BBS/E/I/00007039. Coronavirus sub-genomic mRNA (sgmRNA) synthesis occurs via a process of discontinuous transcription involving complementary transcription regulatory sequences (TRSs), one (TRS-L) encompassing the leader sequence of the 5' untranslated region (UTR), and the other upstream of each structural and accessory gene (TRS-B). Several coronaviruses have an ORF located between the N gene and the 3'-UTR, an area previously thought to be non-coding in the Gammacoronavirus infectious bronchitis virus (IBV) due to a lack of a canonical TRS-B. Here, we identify a non-canonical TRS-B allowing for a novel sgmRNA relating to this ORF to be produced in several strains of IBV: Beaudette, CR88, H120, D1466, Italy-02 and QX. Interestingly, the potential protein produced by this ORF is prematurely truncated in the Beaudette strain. A single nucleotide deletion was made in the Beaudette strain allowing for the generation of a recombinant IBV (rIBV) that had the potential to express a full-length protein. Assessment of this rIBV in vitro demonstrated that restoration of the full-length potential protein had no effect on viral replication. Further assessment of the Beaudette-derived RNA identified a second non-canonically transcribed sgmRNA located within gene 2. Deep sequencing analysis of allantoic fluid from Beaudette-infected embryonated eggs confirmed the presence of both the newly identified non-canonically transcribed sgmRNAs and highlighted the potential for further yet unidentified sgmRNAs. This HiSeq data, alongside the confirmation of non-canonically transcribed sgmRNAs, indicates the potential of the coronavirus genome to encode a larger repertoire of genes than has currently been identified. Publisher PDF

BackgroundNon-targeted whole genome sequencing is a powerful tool to comprehensively identify constituents of microbial communities in a sample. There is no need to direct the analysis to any identification before sequencing which can decrease the introduction of bias and false negatives results. It also allows the assessment of genetic aberrations in the genome (e.g., single nucleotide variants, deletions, insertions and copy number variants) including in noncoding protein regions.MethodsThe performance of four different random priming amplification methods to recover RNA viral genetic material of SARS-CoV-2 were compared in this study. In method 1 (H-P) the reverse transcriptase (RT) step was performed with random hexamers whereas in methods 2-4 RT incorporating an octamer primer with a known tag. In methods 1 and 2 (K-P) sequencing was applied on material derived from the RT-PCR step, whereas in methods 3 (SISPA) and 4 (S-P) an additional amplification was incorporated before sequencing.ResultsThe SISPA method was the most effective and efficient method for non-targeted/random priming whole genome sequencing of COVID that we tested. The SISPA method described in this study allowed for whole genome assembly of SARS-CoV-2 and influenza A(H1N1)pdm09 in mixed samples. We determined the limit of detection and characterization of SARS-CoV-2 virus which was 103 pfu/ml (Ct, 22.4) for whole genome assembly and 101 pfu/ml (Ct, 30) for metagenomics detection.ConclusionsThe SISPA method is predominantly useful for obtaining genome sequences from RNA viruses or investigating complex clinical samples as no prior sequence information is needed. It might be applied to monitor genomic virus changes, virus evolution and can be used for fast metagenomics detection or to assess the general picture of different pathogens within the sample.

Intrinsically disordered regions/proteins (IDRs) are abundant across all the domains of life, where they perform important regulatory roles and supplement the biological functions of structured proteins/regions (SRs). Despite the multifunctionality features of IDRs, several interrogations on the evolution of viral genomic regions encoding IDRs in diverse viral proteins remain unreciprocated. To fill this gap, we benchmarked the findings of two most widely used and reliable intrinsic disorder prediction algorithms (IUPred2A and ESpritz) to a dataset of 6108 reference viral proteomes to unravel the multifaceted evolutionary forces that shape the codon usage in the viral genomic regions encoding for IDRs and SRs. We found persuasive evidence that the natural selection predominantly governs the evolution of codon usage in regions encoding IDRs by most of the viruses. In addition, we confirm not only that codon usage in regions encoding IDRs is less optimized for the protein synthesis machinery (transfer RNAs pool) of their host than for those encoding SRs, but also that the selective constraints imposed by codon bias sustain this reduced optimization in IDRs. Our analysis also establishes that IDRs in viruses are likely to tolerate more translational errors than SRs. All these findings hold true, irrespective of the disorder prediction algorithms used to classify IDRs. In conclusion, our study offers a novel perspective on the evolution of viral IDRs and the evolutionary adaptability to multiple taxonomically divergent hosts.

The full genome sequences of two isolates of bluetongue virus (BTV) from a commercial sheeppox vaccine were determined. Strain SPvvvv/02 shows low sequence identity to its closest relative, strain BTV-26 KUW2010/02, indicating the probable detection of a novel BTV genotype, whereas strain SPvvvv/03 shows high sequence identity to strain BTV-28/1537/14.

Background Hepatocellular carcinoma is the second most deadly cancer with late presentation and limited treatment options, highlighting an urgent need to better understand HCC to facilitate the identification of early-stage biomarkers and uncover therapeutic targets for the development of novel therapies for HCC. Methods Deep transcriptome sequencing of tumor and paired non-tumor liver tissues was performed to comprehensively evaluate the profiles of both the host and HBV transcripts in HCC patients. Differential gene expression patterns and the dys-regulated genes associated with clinical outcomes were analyzed. Somatic mutations were identified from the sequencing data and the deleterious mutations were predicted. Lastly, human-HBV chimeric transcripts were identified, and their distribution, potential function and expression association were analyzed. Results Expression profiling identified the significantly upregulated TP73 as a nodal molecule modulating expression of apoptotic genes. Approximately 2.5% of dysregulated genes significantly correlated with HCC clinical characteristics. Of the 110 identified genes, those involved in post-translational modification, cell division and/or transcriptional regulation were upregulated, while those involved in redox reactions were downregulated in tumors of patients with poor prognosis. Mutation signature analysis identified that somatic mutations in HCC tumors were mainly non-synonymous, frequently affecting genes in the micro-environment and cancer pathways. Recurrent mutations occur mainly in ribosomal genes. The most frequently mutated genes were generally associated with a poorer clinical prognosis. Lastly, transcriptome sequencing suggest that HBV replication in the tumors of HCC patients is rare. HBV-human fusion transcripts are a common observation, with favored HBV and host insertion sites being the HBx C-terminus and gene introns (in tumors) and introns/intergenic-regions (in non-tumors), respectively. HBV-fused genes in tumors were mainly involved in RNA binding while those in non-tumors tissues varied widely. These observations suggest that while HBV may integrate randomly during chronic infection, selective expression of functional chimeric transcripts may occur during tumorigenesis. Conclusions Transcriptome sequencing of HCC patients reveals key cancer molecules and clinically relevant pathways deregulated/mutated in HCC patients and suggests that while HBV may integrate randomly during chronic infection, selective expression of functional chimeric transcripts likely occur during the process of tumorigenesis.

Current high-throughput sequencing technologies can generate sequence data and provide information on the genetic composition of samples at very high coverage. Deep sequencing approaches enable the detection of rare variants in heterogeneous samples, such as viral quasi-species, but also have the undesired effect of amplifying sequencing errors and artefacts. Distinguishing real variants from such noise is not straightforward. Variant callers that can handle pooled samples can be in trouble at extremely high read depths, while at lower depths sensitivity is often sacrificed to specificity. In this paper, we propose SiNPle (Simplified Inference of Novel Polymorphisms from Large coveragE), a fast and effective software for variant calling. SiNPle is based on a simplified Bayesian approach to compute the posterior probability that a variant is not generated by sequencing errors or PCR artefacts. The Bayesian model takes into consideration individual base qualities as well as their distribution, the baseline error rates during both the sequencing and the PCR stage, the prior distribution of variant frequencies and their strandedness. Our approach leads to an approximate but extremely fast computation of posterior probabilities even for very high coverage data, since the expression for the posterior distribution is a simple analytical formula in terms of summary statistics for the variants appearing at each site in the genome. These statistics can be used to filter out putative SNPs and indels according to the required level of sensitivity. We tested SiNPle on several simulated and real-life viral datasets to show that it is faster and more sensitive than existing methods. The source code for SiNPle is freely available to download and compile, or as a Conda/Bioconda package.

Epizootic hemorrhagic disease virus (EHDV) is a Culicoides-transmitted orbivirus that infects domestic and wild ruminants in many parts of the world. Of the eight proposed serotypes, only EHDV-1, 2 and 6 have been reported to be present in the Americas. Following the identification of a virulent EHD-6 reasssortant virus in the USA in 2007 (EHDV-6 Indiana), with outer coat protein segments derived from an Australian strain of EHDV and all remaining segments derived from a locally circulating EHDV-2 strain, questions have remained about the origin of the Australian parent strain and how it may have arrived in the USA. When EHDV-6 was identified in asymptomatic cattle imported into the Caribbean island of Trinidad in 2013, full genome sequencing was carried out to further characterise the virus. The EHDV-6 Trinidad was a reassortant virus, with 8 of its 10 segments, being derived from the same exotic Australian EHDV-6 strain as the VP2 and VP5 present in the EHDV-6 Indiana strain from the USA. Analyses of the two remaining segments revealed that segment 8 showed the highest nucleotide identity (90.4%) with a USA New Jersey strain of EHDV-1, whereas segment 4 had the highest nucleotide identity (96.5%) with an Australian EHDV-2 strain. This data strongly suggests that the Trinidad EHDV-6 has an Australian origin, receiving its segment 4 from a reassortment event with an EHDV-2 also from Australia. This reassortant virus likely came to the Americas, where it received its segment 8 from a locally-circulating (as yet unknown) EHDV strain. This virus then may have gained entry into the USA, where it further reassorted with a known locally-circulating EHDV-2, the resulting strain being EHDV-6 Indiana. This study therefore identifies, for the first time, the likely minor parent virus of the EHDV-6 currently circulating in the USA., Highlights • A unique reassortant EHD-6 was circulating asymptomatically in Trinidad in 2013 • Nine of the ten segments making up the EHD-6 Trinidad virus had a likely Australian origin • The EHDV-6 Trinidad is likely to be the minor parent virus of the EHDV-6 Indiana strain currently circulating in the USA.

The number of available biological databases keeps on increasing every day. One limitation is that these databases are stored in diverse formats. Semantic web technology has introduced the resource description format (RDF) to unify heterogeneous databases. In this chapter, we illustrate how a knowledge graph can be constructed out of the biological RDF databases. We also show how free-text search can be implemented to access nodes in the knowledge graph. Finally, we introduce a way to display and navigate the created knowledge graph.

A large number of biological databases are currently in use by scientists. These databases employ different formats, many of which can be converted into resource description format (RDF), which can be subsequently queried using semantic web methods. These databases have “inter” and “intra” database relationships. RDF has an inherent graph structure that facilitates exploration of connections between data via graphical representations known as knowledge graphs. In this paper, we survey the existing methods that are in use to link biological databases and evaluate the effectiveness with which the available approaches can predict unknown links between entities in databases as a means of improving knowledge graphs.

Background There are a large number of biological databases publicly available for scientists in the web. Also, there are many private databases generated in the course of research projects. These databases are in a wide variety of formats. Web standards have evolved in the recent times and semantic web technologies are now available to interconnect diverse and heterogeneous sources of data. Therefore, integration and querying of biological databases can be facilitated by techniques used in semantic web. Heterogeneous databases can be converted into Resource Description Format (RDF) and queried using SPARQL language. Searching for exact queries in these databases is trivial. However, exploratory searches need customized solutions, especially when multiple databases are involved. This process is cumbersome and time consuming for those without a sufficient background in computer science. In this context, a search engine facilitating exploratory searches of databases would be of great help to the scientific community. Results We present BioCarian, an efficient and user-friendly search engine for performing exploratory searches on biological databases. The search engine is an interface for SPARQL queries over RDF databases. We note that many of the databases can be converted to tabular form. We first convert the tabular databases to RDF. The search engine provides a graphical interface based on facets to explore the converted databases. The facet interface is more advanced than conventional facets. It allows complex queries to be constructed, and have additional features like ranking of facet values based on several criteria, visually indicating the relevance of a facet value and presenting the most important facet values when a large number of choices are available. For the advanced users, SPARQL queries can be run directly on the databases. Using this feature, users will be able to incorporate federated searches of SPARQL endpoints. We used the search engine to do an exploratory search on previously published viral integration data and were able to deduce the main conclusions of the original publication. BioCarian is accessible via http://www.biocarian.com. Conclusions We have developed a search engine to explore RDF databases that can be used by both novice and advanced users. Electronic supplementary material The online version of this article (doi:10.1186/s12859-017-1840-4) contains supplementary material, which is available to authorized users.

The number of biological databases available both in the public domain and in private keep on increasing every day. Scientists and researchers need to analyze and make use of the data stored in different databases. One limitation is that these databases are stored in diverse formats. However, semantic web methods have introduced the Resource description format (RDF) to unify heterogeneous databases. In this paper we illustrate how to construct a knowledge graph out of biological RDF databases by connecting possibly related data. We also show how the resulting knowledge graph can be made compact. We, then show how free-text search can be implemented to access nodes in the knowledge graph. Finally, we introduce a way to display and navigate the created knowledge graph.

The study of virus integrations in human genome is important since virus integrations were shown to be associated with diseases. In the literature, few methods have been proposed that predict virus integrations using next generation sequencing datasets. Although they work, they are slow and are not very sensitive. This paper introduces a new method BatVI to predict viral integrations. Our method uses a fast screening method to filter out chimeric reads containing possible viral integrations. Next, sensitive alignments of these candidate chimeric reads are called by BLAST. Chimeric reads that are co-localized in the human genome are clustered. Finally, by assembling the chimeric reads in each cluster, high confident virus integration sites are extracted. We compared the performance of BatVI with existing methods VirusFinder and VirusSeq using both simulated and real-life datasets of liver cancer patients. BatVI ran an order of magnitude faster and was able to predict almost twice the number of true positives compared to other methods while maintaining a false positive rate less than 1%. For the liver cancer datasets, BatVI uncovered novel integrations to two important genes TERT and MLL4, which were missed by previous studies. Through gene expression data, we verified the correctness of these additional integrations. BatVI can be downloaded from http://biogpu.ddns.comp.nus.edu.sg/~ksung/batvi/index.html .

There are over 1600 publicly available biological databases, and this number is growing at a steady rate. These databases are not in a uniform format, however, web-based technologies can be employed to integrate them. One of the key steps in enabling semantic web techniques is to convert these databases into a uniform format, for example, that of the Resource Description Framework (RDF). There are already several biological databases available in RDF format. However, some of the major databases are only found in custom formats. In this paper, we review the methods that are available to explore biological databases in RDF format. We also review current projects that facilitate the conversion of biological data into RDF format. We will identify the strengths and weaknesses of the current exploratory methods and suggest improvements that will enable both novice and expert users to search biological databases more effectively.

Structural variations (SVs) play a crucial role in genetic diversity. However, the alignments of reads near/across SVs are made inaccurate by the presence of polymorphisms. BatAlign is an algorithm that integrated two strategies called ‘Reverse-Alignment’ and ‘Deep-Scan’ to improve the accuracy of read-alignment. In our experiments, BatAlign was able to obtain the highest F-measures in read-alignments on mismatch-aberrant, indel-aberrant, concordantly/discordantly paired and SV-spanning data sets. On real data, the alignments of BatAlign were able to recover 4.3% more PCR-validated SVs with 73.3% less callings. These suggest BatAlign to be effective in detecting SVs and other polymorphic-variants accurately using high-throughput data. BatAlign is publicly available at https://goo.gl/a6phxB.

The transition from chronic phase (CP) to blast crisis (BC) chronic myeloid leukemia (CML) is characterized by reprogramming of the CML transcriptome (Radich et al. PNAS 2006), and shortened survival. Current models propose genomic instability as causal in BC transformation with enhanced DNA damage and impaired DNA repair inducing genetic mutations (ranging from large chromosomal aberrations to point mutations), altered gene function, and eventually BC transformation (Perrotti et al. JCI 2010). Consistent with this model are the phenomena of BC clonal evolution, and the increased frequency of ABL kinase domain mutations found in BC. Because different mutational processes are associated with distinct cancer-specific mutation signatures (Alexandrov et al. Nature 2013), this model also predicts the existence of a CML-specific mutation signature. In addition, recent work has highlighted the importance of epigenetic alterations in hematologic malignancies (Shih et al., Nat. Rev. Cancer, 2012). However, we lack a complete understanding of the type or frequency of genetic alterations in BC, and the relative contribution of genetic vs. epigenetic events in reprogramming the BC transcriptome. To address these knowledge gaps, we analyzed the CML progression genome, epigenome, and transcriptome in 12 CP/BC sample pairs. Whole-genome sequencing revealed the CML genome to be relatively stable with respect to structural variations, indels, and somatic single nucleotide variants. The average number of nonsynonymous coding mutations per BC genome was 5, placing the BC coding genome in the same mutation frequency range as AML and ALL genomes (Alexandrov et al. Nature 2013). In addition, we identified a novel mutation signature in all CML samples suggesting a CML-specific mutational process. 1175 genes were 'hit' by genomic, mostly copy number, alterations in >1 sample, and included TCR genes and Ikaros (IKZF1) among lymphoid BC pairs. Only 21 recurrently altered genes were affected by somatic SNVs or indels, with resistance-associated ABL1 mutations being commonest. We next used DNA methylation arrays to assess the BC epigenome, and found 20,651 CpG sites (out of 455,187) to be hyper-methylated, and 3225 to be hypo-methylated in BC compared to CP. Combined methylome and transcriptome analysis demonstrated an inverse relationship between methylation and expression changes at a subset of CpG sites enriched at promoters. Genes with increased methylation/decreased expression or decreased methylation/increased expression included those involved in cell cycle control/heme biosynthesis, and molecular mechanisms of cancer/G-protein coupled receptor signaling/MAPK signaling respectively. Unsupervised methylation-based clustering segregated samples into CP, lymphoid BC and myeloid BC groups, recapitulating expression-based clustering, and further supporting a functional role for DNA methylation in BC transcriptional reprogramming. We next performed an integrative analysis by combining the genome, methylome, and transcriptome datasets, and included data from 34 additional CML samples. Top ranking candidate genes included epigenetic modifiers, and hematopoetic differentiation- and stem cell-related genes. Functional analysis of candidate genes and epigenetic processes using genetic and epigenetic drug-based approaches are ongoing. In summary, we conclude that: 1. The genomic and epigenomic landscapes in BC are characterized by a modest number of recurring events in the former, but consistent and striking differences in the latter, 2. The BC methylome is functionally associated with the robust gene expression changes found in BC, and 3. Epigenetic modifier drugs may be of use in reversing the gene expression changes characteristic of BC. Disclosures Chuah: Children International: Honoraria; Novartis: Honoraria; Bristol Meyers Squibb: Honoraria. Takahashi:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Sysmex: Research Funding, Speakers Bureau; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Speakers Bureau; Masis: Consultancy; Otsuka: Membership on an entity's Board of Directors or advisory committees; Astellas: Speakers Bureau; BMS: Honoraria, Research Funding, Speakers Bureau.

Current models of CML blast crisis (BC) propose that expression of BCR-ABL results in genomic instability and the acquisition of genetic alterations that affect cell proliferation and survival, self-renewal and differentiation. To characterize the molecular events that underlie progression, we performed whole genome sequencing of paired samples of the same patient at CP and at BC (n = 12), as well as expression and methylation arrays of these samples and a larger validation cohort of unpaired CD34-selected samples (n = 38). Contrary to expectations, we found that the CML BC genome is relatively quiescent with regards to SNVs, indels and structural variations. In contrast, we observed widespread hyper-methylation in BC that was associated with distinct changes in expression and was independent of lineage/differentiation state. These findings suggest that in addition to genetic alterations, epigenomic events are likely to contribute substantively to BC progression. To understand the functional effects of the dysregulated transcriptome and epigenome in BC CML, we employed both pharmacologic and genetic methods to target candidate genes of interest identified in our earlier studies. To induce de-methylation of the BC genome, we treated primary samples with low doses of decitabine, a DNMT inhibitor. We found that decitabine impaired colony formation ability of BC CD34+ progenitors and concomitantly activated regulators of myeloid differentiation that were both hyper-methylated and down-regulated in BC CD34+ progenitors, such as MPO and KLF1. These results suggest that hyper-methylation does contribute to BC CD34+ progenitor function, and support the use of epigenetic therapies as a rational approach to targeting BC. The genetic approach we chose was a CRISPR-based in vitro pooled screen. We created a custom library targeting 200 genes, with an average of 5 sgRNAs per gene, and 50 non-targeting controls. We transduced K562 with the library and harvested samples at different time-points post-transduction/selection - Day 0, 7 and 21 - for deep sequencing. As expected, sgRNAs targeting essential genes such as MYC and MCM 2-7 were recurrently depleted in the population over time. More importantly, enriched sgRNAs targeted genes including TET2, which has been previously reported to be inactivated in myeloid malignancies, as well as novel candidates including RREB1, a transcription factor that binds to RAS-responsive elements (RREs) and may be involved in MAPK signaling. We will validate these targets by knocking them out individually and assessing their effect on the ability of CP cells to serially replate and/or engraft immune-deficient mice. Disclosures Chuah: Bristol-Myers Squibb: Honoraria; Novartis: Honoraria; Chiltern International: Honoraria. Takahashi:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; BMS: Honoraria, Research Funding, Speakers Bureau; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Masis: Consultancy; Otsuka: Membership on an entity's Board of Directors or advisory committees; Celgene: Speakers Bureau; Sysmex: Research Funding, Speakers Bureau; Astellas: Speakers Bureau. Valent:Novartis: Consultancy, Honoraria, Research Funding; Ariad: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria; Pfizer: Honoraria; Celgene: Honoraria.