The External RNA Controls Consortium: a progress report

Baker, Shawn C.; Bauer, Steven R.; Beyer, Richard P.; Brenton, James D.; Bromley, Bud; Burrill, John; Causton, Helen C.; Conley, Michael; Elespuru, Rosalie K.; Fero, M.J.; Foy, Carole A.; Fuscoe, James C.; Gao, Xiaolian; Gerhold, David; Gilles, Patrick N.; Goodsaid, Federico; Guo, Xu; Hackett, Joe; Hockett, Richard D.; Ikonomi, Pranvera; Irizarry, Rafael A.; Kawasaki, Ernest S.; Kaysser-Kranich, Tamma; Kerr, Kathleen F.; Kiser, Gretchen L.; Koch, Walter; Lee, Kathy; Liu, Chunmei; Liu, Z Lewis; Lucas, Anne Bergstrom; Manohar, Chitra F.; Miyada, G.; Modrušan, Zora; Parkes, Helen C.; Puri, Raj K.; Reid, Laura; Ryder, Thomas B.; Salit, Marc; Samaha, Raymond R.; Scherf, Uwe; Sendera, Timothy J.; Setterquist, Robert A.; Shi, Leming; Shippy, Richard; Soriano, Jesús V.; Wagar, Elizabeth A.; Warrington, Janet A.; Williams, Mickey; Wilmer, Frederike; Wilson, Mike; Wolber, Paul K.; Wu, Xiaoning; Zadro, Renata

doi:10.1038/nmeth1005-731

Cited by 331 publications

(138 citation statements)

References 7 publications

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“…We utilized the known quantities of RNA spiked-in controls to set a threshold below which we consider the expression readings and transcript assemblies likely unreliable. The spike-in controls used were External RNA Controls Consortium (ERCC) RNAs (Baker et al 2005). These consist of a set of unlabeled, polyadenylated transcripts of differing sizes and concentrations in order to measure against defined performance criteria.…”

Section: Resultsmentioning

confidence: 99%

Improved definition of the mouse transcriptome via targeted RNA sequencing

et al. 2016

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Targeted RNA sequencing (CaptureSeq) uses oligonucleotide probes to capture RNAs for sequencing, providing enriched read coverage, accurate measurement of gene expression, and quantitative expression data. We applied CaptureSeq to refine transcript annotations in the current murine GRCm38 assembly. More than 23,000 regions corresponding to putative or annotated long noncoding RNAs (lncRNAs) and 154,281 known splicing junction sites were selected for targeted sequencing across five mouse tissues and three brain subregions. The results illustrate that the mouse transcriptome is considerably more complex than previously thought. We assemble more complete transcript isoforms than GENCODE, expand transcript boundaries, and connect interspersed islands of mapped reads. We describe a novel filtering pipeline that identifies previously unannotated but high-quality transcript isoforms. In this set, 911 GENCODE neighboring genes are condensed into 400 expanded gene models. Additionally, 594 GENCODE lncRNAs acquire an open reading frame (ORF) when their structure is extended with CaptureSeq. Finally, we validate our observations using current FANTOM and Mouse ENCODE resources.

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Section: Resultsmentioning

confidence: 99%

Improved definition of the mouse transcriptome via targeted RNA sequencing

et al. 2016

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“…This final design covered 36.8 Mb and targets both 39 and 59 100-nt termini for 76.4% (206,747) publicly annotated introns or a single terminus for 90.2% (244,125) introns. Additional control probes, including probes targeting all ERCC controls (Baker et al 2005), were included within the design to assess CaptureSeq performance. The final design was manufactured on a Custom Sequence 2.1M Array (Roche/NimbleGen; Cat #05329841001).…”

Section: Capture Array Designmentioning

confidence: 99%

Genome-wide discovery of human splicing branchpoints

et al. 2015

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During the splicing reaction, the 59 intron end is joined to the branchpoint nucleotide, selecting the next exon to incorporate into the mature RNA and forming an intron lariat, which is excised. Despite a critical role in gene splicing, the locations and features of human splicing branchpoints are largely unknown. We use exoribonuclease digestion and targeted RNA-sequencing to enrich for sequences that traverse the lariat junction and, by split and inverted alignment, reveal the branchpoint. We identify 59,359 high-confidence human branchpoints in >10,000 genes, providing a first map of splicing branchpoints in the human genome. Branchpoints are predominantly adenosine, highly conserved, and closely distributed to the 39 splice site. Analysis of human branchpoints reveals numerous novel features, including distinct features of branchpoints for alternatively spliced exons and a family of conserved sequence motifs overlapping branchpoints we term B-boxes, which exhibit maximal nucleotide diversity while maintaining interactions with the keto-rich U2 snRNA. Different B-box motifs exhibit divergent usage in vertebrate lineages and associate with other splicing elements and distinct intron-exon architectures, suggesting integration within a broader regulatory splicing code. Lastly, although branchpoints are refractory to common mutational processes and genetic variation, mutations occurring at branchpoint nucleotides are enriched for disease associations.[Supplemental material is available for this article.]The majority of human genes are spliced, a process whereby introns are removed from the nascent RNA and the remaining exonic sequence joined together into a mature RNA transcript. In addition, alternative splicing generates complex networks of isoforms from human gene loci and plays a major role in shaping the diversity of the transcriptome (Kapranov et al. 2005;Gerstein et al. 2007;Djebali et al. 2012).Splicing occurs in the spliceosome, a large ribonucleoprotein complex that recognizes at least three genetic elements within each intron: the 59 splice site (59SS), the 39 splice site (39SS), and the branchpoint (Will and L€ uhrmann 2011). RNU2-1, the U2 spliceosomal RNA (snRNA) base pairs to the sequence surrounding the unpaired branchpoint nucleotide, which then undergoes transesterification with the 59 end of the intron to form a closed lariat structure. The spliceosome then scans for the downstream 39 splice site, which undergoes a second trans-esterification reaction to join together the two exon ends and excise the intron lariat (Fig.

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“…One way to deal with this is to use a general common reference. 52 To facilitate the comparison of datasets, initiatives have been taken to investigate the differences in array data gathered on different platforms 53 and to agree on a reference standard to facilitate the comparison of data sets. 52 Apart from this, it is important to note that the dissimilarities identified are the results of comparisons made at the level of individual genes.…”

Section: Integration Of Genome-wide Expression Data Setsmentioning

confidence: 99%

“…52 To facilitate the comparison of datasets, initiatives have been taken to investigate the differences in array data gathered on different platforms 53 and to agree on a reference standard to facilitate the comparison of data sets. 52 Apart from this, it is important to note that the dissimilarities identified are the results of comparisons made at the level of individual genes. Because subtle changes in single gene expression levels may act in concert to result in significant changes at the pathway level, it may be worthwhile to transcend from the differential expression of individual genes to the identification of important biological processes underlying atherosclerosis.…”

Section: Integration Of Genome-wide Expression Data Setsmentioning

confidence: 99%

Genome-Wide Expression Studies of Atherosclerosis

Bijnens

Lutgens

Ayoubi

et al. 2006

ATVB

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Abstract-During the past 6 years, gene expression profiling of atherosclerosis has been used to identify genes and pathways relevant in vascular (patho)physiology. This review discusses some critical issues in the methodology, analysis, and interpretation of the data of gene expression studies that have made use of vascular specimens from animal models and humans. Analysis of gene expression studies has evolved toward the genome-wide expression profiling of large series of individual samples of well-characterized donors. Despite the advances in statistical and bioinformatical analysis of expression data sets, studies have not yet fully exploited the potential of gene expression data sets to obtain novel insights into the molecular mechanisms underlying atherosclerosis. To assess the potential of published expression data, we compared the data of a CC chemokine gene cluster between 18 murine and human gene expression profiling articles. Our analysis revealed that an adequate comparison is mainly hindered by the incompleteness of available data sets. The challenge for future vascular genomic profiling studies will be to further improve the experimental design, statistical, and bioinformatical analysis and to make data sets freely accessible.

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The External RNA Controls Consortium: a progress report

Cited by 331 publications

References 7 publications

Improved definition of the mouse transcriptome via targeted RNA sequencing

Improved definition of the mouse transcriptome via targeted RNA sequencing

Genome-wide discovery of human splicing branchpoints

Genome-Wide Expression Studies of Atherosclerosis

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