In-Depth Transcriptome Analysis Reveals Novel TARs and Prevalent Antisense Transcription in Human Cell Lines

Several recent studies have indicated that transcription is pervasive in regions outside of protein coding genes and that short antisense transcripts can originate from the promoter and terminator regions of genes. Here we investigate transcription of fragments longer than 200 nucleotides, focusing on antisense transcription for known protein coding genes and intergenic transcription. We find that roughly 12% to 16% of all reads that originate from promoter and terminator regions, respectively, map antisense to the gene in question. Furthermore, we detect a high number of novel transcriptionally active regions (TARs) that are generally expressed at a lower level than protein coding genes. We find that the correlation between RNA-seq data and microarray data is dependent on the gene length, with longer genes showing a better correlation. We detect high antisense transcriptional activity from promoter, terminator and intron regions of protein-coding genes and identify a vast number of previously unidentified TARs, including putative novel EGFR transcripts. This shows that in-depth analysis of the transcriptome using RNA-seq is a valuable tool for understanding complex transcriptional events. Furthermore, the development of new algorithms for estimation of gene expression from RNA-seq data is necessary to minimize length bias

Automation of cDNA Synthesis and Labelling Improves Reproducibility

Background. Several technologies, such as in-depth sequencing and microarrays, enable large-scale interrogation of genomes and transcriptomes. In this study, we asses reproducibility and throughput by moving all laboratory procedures to a robotic workstation, capable of handling superparamagnetic beads. Here, we describe a fully automated procedure for cDNA synthesis and labelling for microarrays, where the purification steps prior to and after labelling are based on precipitation of DNA on carboxylic acid-coated paramagnetic beads. Results. The fully automated procedure allows for samples arrayed on a microtiter plate to be processed in parallel without manual intervention and ensuring high reproducibility. We compare our results to a manual sample preparation procedure and, in addition, use a comprehensive reference dataset to show that the protocol described performs better than similar manual procedures. Conclusions. We demonstrate, in an automated gene expression microarray experiment, a reduced variance between replicates, resulting in an increase in the statistical power to detect differentially expressed genes, thus allowing smaller differences between samples to be identified. This protocol can with minor modifications be used to create cDNA libraries for other applications such as in-depth analysis using next-generation sequencing technologies

Study design requirements for RNA sequencing-based breast cancer diagnostics

Sequencing-based molecular characterization of tumors provides information required for individualized cancer treatment. There are well-defined molecular subtypes of breast cancer that provide improved prognostication compared to routine biomarkers. However, molecular subtyping is not yet implemented in routine breast cancer care. Clinical translation is dependent on subtype prediction models providing high sensitivity and specificity. In this study we evaluate sample size and RNA-sequencing read requirements for breast cancer subtyping to facilitate rational design of translational studies. We applied subsampling to ascertain the effect of training sample size and the number of RNA sequencing reads on classification accuracy of molecular subtype and routine biomarker prediction models (unsupervised and supervised). Subtype classification accuracy improved with increasing sample size up to N = 750 (accuracy = 0.93), although with a modest improvement beyond N = 350 (accuracy = 0.92). Prediction of routine biomarkers achieved accuracy of 0.94 (ER) and 0.92 (Her2) at N = 200. Subtype classification improved with RNA-sequencing library size up to 5 million reads. Development of molecular subtyping models for cancer diagnostics requires well-designed studies. Sample size and the number of RNA sequencing reads directly influence accuracy of molecular subtyping. Results in this study provide key information for rational design of translational studies aiming to bring sequencing-based diagnostics to the clinic.NonePublishe

Determining breast cancer histological grade from RNA-sequencing data

BACKGROUND: The histologic grade (HG) of breast cancer is an established prognostic factor. The grade is usually reported on a scale ranging from 1 to 3, where grade 3 tumours are the most aggressive. However, grade 2 is associated with an intermediate risk of recurrence, and carries limited information for clinical decision-making. Patients classified as grade 2 are at risk of both under- and over-treatment. METHODS: RNA-sequencing analysis was conducted in a cohort of 275 women diagnosed with invasive breast cancer. Multivariate prediction models were developed to classify tumours into high and low transcriptomic grade (TG) based on gene- and isoform-level expression data from RNA-sequencing. HG2 tumours were reclassified according to the prediction model and a recurrence-free survival analysis was performed by the multivariate Cox proportional hazards regression model to assess to what extent the TG model could be used to stratify patients. The prediction model was validated in N=487 breast cancer cases from the The Cancer Genome Atlas (TCGA) data set. Differentially expressed genes and isoforms associated with HGs were analysed using linear models. RESULTS: The classification of grade 1 and grade 3 tumours based on RNA-sequencing data achieved high accuracy (area under the receiver operating characteristic curve = 0.97). The association between recurrence-free survival rate and HGs was confirmed in the study population (hazard ratio of grade 3 versus 1 was 2.62 with 95 % confidence interval = 1.04-6.61). The TG model enabled us to reclassify grade 2 tumours as high TG and low TG gene or isoform grade. The risk of recurrence in the high TG group of grade 2 tumours was higher than in low TG group (hazard ratio = 2.43, 95 % confidence interval = 1.13-5.20). We found 8200 genes and 13,809 isoforms that were differentially expressed between HG1 and HG3 breast cancer tumours. CONCLUSIONS: Gene- and isoform-level expression data from RNA-sequencing could be utilised to differentiate HG1 and HG3 tumours with high accuracy. We identified a large number of novel genes and isoforms associated with HG. Grade 2 tumours could be reclassified as high and low TG, which has the potential to reduce over- and under-treatment if implemented clinically.NonePublishe

Exome sequencing of contralateral breast cancer identifies metastatic disease

Women with contralateral breast cancer (CBC) have significantly worse prognosis compared to women with unilateral cancer. A possible explanation of the poor prognosis of patients with CBC is that in a subset of patients, the second cancer is not a new primary tumor but a metastasis of the first cancer that has potentially obtained aggressive characteristics through selection of treatment. Exome and whole-genome sequencing of solid tumors has previously been used to investigate the clonal relationship between primary tumors and metastases in several diseases. In order to assess the relationship between the first and the second cancer, we performed exome sequencing to identify somatic mutations in both first and second cancers, and compared paired normal tissue of 25 patients with metachronous CBC. For three patients, we identified shared somatic mutations indicating a common clonal origin thereby demonstrating that the second tumor is a metastasis of the first cancer, rather than a new primary cancer. Accordingly, these patients all developed distant metastasis within 3 years of the second diagnosis, compared with 7 out of 22 patients with non-shared somatic profiles. Genomic profiling of both tumors help the clinicians distinguish between true CBCs and subsequent metastasesVetenskapsrådetForteAccepte

Genome-wide profiling of Populus small RNAs

<p>Abstract</p> <p>Background</p> <p>Short RNAs, and in particular microRNAs, are important regulators of gene expression both within defined regulatory pathways and at the epigenetic scale. We investigated the short RNA (sRNA) population (18-24 nt) of the transcriptome of green leaves from the sequenced <it>Populus trichocarpa </it>using a concatenation strategy in combination with 454 sequencing.</p> <p>Results</p> <p>The most abundant size class of sRNAs were 24 nt. Long Terminal Repeats were particularly associated with 24 nt sRNAs. Additionally, some repetitive elements were associated with 22 nt sRNAs. We identified an sRNA hot-spot on chromosome 19, overlapping a region containing both the proposed sex-determining locus and a major cluster of <it>NBS-LRR </it>genes. A number of phased siRNA loci were identified, a subset of which are predicted to target PPR and <it>NBS-LRR </it>disease resistance genes, classes of genes that have been significantly expanded in <it>Populus</it>. Additional loci enriched for sRNA production were identified and characterised. We identified 15 novel predicted microRNAs (miRNAs), including miRNA*sequences, and identified a novel locus that may encode a dual miRNA or a miRNA and short interfering RNAs (siRNAs).</p> <p>Conclusions</p> <p>The short RNA population of <it>P. trichocarpa </it>is at least as complex as that of <it>Arabidopsis thaliana</it>. We provide a first genome-wide view of short RNA production for <it>P. trichocarpa </it>and identify new, non-conserved miRNAs.</p

Sequencing of breast cancer stem cell populations indicates a dynamic conversion between differentiation states in vivo

Peer reviewe

Methodology Report Automation of cDNA Synthesis and Labelling Improves Reproducibility

Background. Several technologies, such as in-depth sequencing and microarrays, enable large-scale interrogation of genomes and transcriptomes. In this study, we asses reproducibility and throughput by moving all laboratory procedures to a robotic workstation, capable of handling superparamagnetic beads. Here, we describe a fully automated procedure for cDNA synthesis and labelling for microarrays, where the purification steps prior to and after labelling are based on precipitation of DNA on carboxylic acid-coated paramagnetic beads. Results. The fully automated procedure allows for samples arrayed on a microtiter plate to be processed in parallel without manual intervention and ensuring high reproducibility. We compare our results to a manual sample preparation procedure and, in addition, use a comprehensive reference dataset to show that the protocol described performs better than similar manual procedures. Conclusions. We demonstrate, in an automated gene expression microarray experiment, a reduced variance between replicates, resulting in an increase in the statistical power to detect differentially expressed genes, thus allowing smaller differences between samples to be identified. This protocol can with minor modifications be used to create cDNA libraries for other applications such as in-depth analysis using next-generation sequencing technologies

Sequencing-based breast cancer diagnostics as an alternative to routine biomarkers

Sequencing-based breast cancer diagnostics have the potential to replace routine biomarkers and provide molecular characterization that enable personalized precision medicine. Here we investigate the concordance between sequencing-based and routine diagnostic biomarkers and to what extent tumor sequencing contributes clinically actionable information. We applied DNA- and RNA-sequencing to characterize tumors from 307 breast cancer patients with replication in up to 739 patients. We developed models to predict status of routine biomarkers (ER, HER2,Ki-67, histological grade) from sequencing data. Non-routine biomarkers, including mutations in BRCA1, BRCA2 and ERBB2(HER2), and additional clinically actionable somatic alterations were also investigated. Concordance with routine diagnostic biomarkers was high for ER status (AUC = 0.95;AUC(replication) = 0.97) and HER2 status (AUC = 0.97;AUC(replication) = 0.92). The transcriptomic grade model enabled classification of histological grade 1 and histological grade 3 tumors with high accuracy (AUC = 0.98;AUC(replication) = 0.94). Clinically actionable mutations in BRCA1, BRCA2 and ERBB2(HER2) were detected in 5.5% of patients, while 53% had genomic alterations matching ongoing or concluded breast cancer studies. Sequencing-based molecular profiling can be applied as an alternative to histopathology to determine ER and HER2 status, in addition to providing improved tumor grading and clinically actionable mutations and molecular subtypes. Our results suggest that sequencing-based breast cancer diagnostics in a near future can replace routine biomarkersNonePublishe

Increased Throughput by Parallelization of Library Preparation for Massive Sequencing

Background: Massively parallel sequencing systems continue to improve on data output, while leaving labor-intensive library preparations a potential bottleneck. Efforts are currently under way to relieve the crucial and time-consuming work to prepare DNA for high-throughput sequencing. Methodology/Principal Findings: In this study, we demonstrate an automated parallel library preparation protocol using generic carboxylic acid-coated superparamagnetic beads and polyethylene glycol precipitation as a reproducible and flexible method for DNA fragment length separation. With this approach the library preparation for DNA sequencing can easily be adjusted to a desired fragment length. The automated protocol, here demonstrated using the GS FLX Titanium instrument, was compared to the standard manual library preparation, showing higher yield, throughput and great reproducibility. In addition, 12 libraries were prepared and uniquely tagged in parallel, and the distribution of sequence reads between these indexed samples could be improved using quantitative PCR-assisted pooling. Conclusions/Significance: We present a novel automated procedure that makes it possible to prepare 36 indexed libraries per person and day, which can be increased to up to 96 libraries processed simultaneously. The yield, speed and robust performance of the protocol constitute a substantial improvement to present manual methods, without the need of extensive equipment investments. The described procedure enables a considerable efficiency increase for small to midsiz