Veal C.D.,University of Leicester |
Freeman P.J.,University of Leicester |
Jacobs K.,U.S. National Cancer Institute |
Jacobs K.,SAIC |
And 10 more authors.
Background: For many analytical methods the efficiency of DNA amplification varies across the genome and between samples. The most affected genome regions tend to correlate with high C + G content, however this relationship is complex and does not explain why the direction and magnitude of effects varies considerably between samples.Results: Here, we provide evidence that sequence elements that are particularly high in C + G content can remain annealed even when aggressive melting conditions are applied. In turn, this behavior creates broader 'Thermodynamically Ultra-Fastened' (TUF) regions characterized by incomplete denaturation of the two DNA strands, so reducing amplification efficiency throughout these domains.Conclusions: This model provides a mechanistic explanation for why some genome regions are particularly difficult to amplify and assay in many procedures, and importantly it also explains inter-sample variability of this behavior. That is, DNA samples of varying quality will carry more or fewer nicks and breaks, and hence their intact TUF regions will have different lengths and so be differentially affected by this amplification suppression mechanism - with 'higher' quality DNAs being the most vulnerable. A major practical consequence of this is that inter-region and inter-sample variability can be largely overcome by employing routine fragmentation methods (e.g. sonication or restriction enzyme digestion) prior to sample amplification. © 2012 Veal et al.; licensee BioMed Central Ltd. Source
Thompson R.,Newcastle University |
Johnston L.,Newcastle University |
Taruscio D.,Istituto Superiore di Sanita |
Monaco L.,Fondazione Telethon |
And 15 more authors.
Journal of General Internal Medicine
Research into rare diseases is typically fragmented by data type and disease. Individual efforts often have poor interoperability and do not systematically connect data across clinical phenotype, genomic data, biomaterial availability, and research/trial data sets. Such data must be linked at both an individual-patient and whole-cohort level to enable researchers to gain a complete view of their disease and patient population of interest. Data access and authorization procedures are required to allow researchers in multiple institutions to securely compare results and gain new insights. Funded by the European Union's Seventh Framework Programme under the International Rare Diseases Research Consortium (IRDiRC), RD-Connect is a global infrastructure project initiated in November 2012 that links genomic data with registries, biobanks, and clinical bioinformatics tools to produce a central research resource for rare diseases. © 2014 Society of General Internal Medicine. Source
De Almeida S.F.,University of Lisbon |
Grosso A.R.,University of Lisbon |
Koch F.,French Institute of Health and Medical Research |
Fenouil R.,French Institute of Health and Medical Research |
And 9 more authors.
Nature Structural and Molecular Biology
Several lines of recent evidence support a role for chromatin in splicing regulation. Here, we show that splicing can also contribute to histone modification, which implies bidirectional communication between epigenetic mechanisms and RNA processing. Genome-wide analysis of histone methylation in human cell lines and mouse primary T cells reveals that intron-containing genes are preferentially marked with histone H3 Lys36 trimethylation (H3K36me3) relative to intronless genes. In intron-containing genes, H3K36me3 marking is proportional to transcriptional activity, whereas in intronless genes, H3K36me3 is always detected at much lower levels. Furthermore, splicing inhibition impairs recruitment of H3K36 methyltransferase HYPB (also known as Setd2) and reduces H3K36me3, whereas splicing activation has the opposite effect. Moreover, the increase of H3K36me3 correlates with the length of the first intron, consistent with the view that splicing enhances H3 methylation. We propose that splicing is mechanistically coupled to recruitment of HYPB/Setd2 to elongating RNA polymerase II. © 2011 Nature America, Inc. All rights reserved. (c) 2011 Nature America, Inc. All rights reserved. Source
Mundry M.,Westfaelische Wilhelms University |
Bornberg-Bauer E.,Westfaelische Wilhelms University |
Sammeth M.,Center Nacional dAnalisi Genomica |
Feulner P.G.D.,Westfaelische Wilhelms University
Background: The quantity of transcriptome data is rapidly increasing for non-model organisms. As sequencing technology advances, focus shifts towards solving bioinformatic challenges, of which sequence read assembly is the first task. Recent studies have compared the performance of different software to establish a best practice for transcriptome assembly. Here, we adapted a simulation approach to evaluate specific features of assembly programs on 454 data. The novelty of our study is that the simulation allows us to calculate a model assembly as reference point for comparison. Findings: The simulation approach allows us to compare basic metrics of assemblies computed by different software applications (CAP3, MIRA, Newbler, and Oases) to a known optimal solution. We found MIRA and CAP3 are conservative in merging reads. This resulted in comparably high number of short contigs. In contrast, Newbler more readily merged reads into longer contigs, while Oases produced the overall shortest assembly. Due to the simulation approach, reads could be traced back to their correct placement within the transcriptome. Together with mapping reads onto the assembled contigs, we were able to evaluate ambiguity in the assemblies. This analysis further supported the conservative nature of MIRA and CAP3, which resulted in low proportions of chimeric contigs, but high redundancy. Newbler produced less redundancy, but the proportion of chimeric contigs was higher. Conclusion: Our evaluation of four assemblers suggested that MIRA and Newbler slightly outperformed the other programs, while showing contrasting characteristics. Oases did not perform very well on the 454 reads. Our evaluation indicated that the software was either conservative (MIRA) or liberal (Newbler) about merging reads into contigs. This suggested that in choosing an assembly program researchers should carefully consider their follow up analysis and consequences of the chosen approach to gain an assembly. © 2012 Mundry et al. Source
Eizirik D.L.,Free University of Colombia |
Sammeth M.,Center Nacional dAnalisi Genomica |
Bouckenooghe T.,Free University of Colombia |
Bottu G.,Free University of Colombia |
And 17 more authors.
Type 1 diabetes (T1D) is an autoimmune disease in which pancreatic beta cells are killed by infiltrating immune cells and by cytokines released by these cells. Signaling events occurring in the pancreatic beta cells are decisive for their survival or death in diabetes. We have used RNA sequencing (RNA-seq) to identify transcripts, including splice variants, expressed in human islets of Langerhans under control conditions or following exposure to the pro-inflammatory cytokines interleukin-1β (IL-1β) and interferon-γ (IFN-γ). Based on this unique dataset, we examined whether putative candidate genes for T1D, previously identified by GWAS, are expressed in human islets. A total of 29,776 transcripts were identified as expressed in human islets. Expression of around 20% of these transcripts was modified by pro-inflammatory cytokines, including apoptosis- and inflammation-related genes. Chemokines were among the transcripts most modified by cytokines, a finding confirmed at the protein level by ELISA. Interestingly, 35% of the genes expressed in human islets undergo alternative splicing as annotated in RefSeq, and cytokines caused substantial changes in spliced transcripts. Nova1, previously considered a brain-specific regulator of mRNA splicing, is expressed in islets and its knockdown modified splicing. 25/41 of the candidate genes for T1D are expressed in islets, and cytokines modified expression of several of these transcripts. The present study doubles the number of known genes expressed in human islets and shows that cytokines modify alternative splicing in human islet cells. Importantly, it indicates that more than half of the known T1D candidate genes are expressed in human islets. This, and the production of a large number of chemokines and cytokines by cytokine-exposed islets, reinforces the concept of a dialog between pancreatic islets and the immune system in T1D. This dialog is modulated by candidate genes for the disease at both the immune system and beta cell level. © 2012 Eizirik et al. Source