WEBINAR: Controlling RNA-Seq Experiments Using Spike-In RNA Variants

Lukas Paul, PhD

Head of Services, Lexogen

Hardly anyone would run an RNA gel without a ladder, but transcriptomes are mostly sequenced without the use of external standards. The added layer of transcript isoform complexity in eukaryotes as well as incomplete or incorrect gene annotations further challenge RNA-Seq pipelines to correctly calculate and compare gene expression values. Lexogen, a specialized transcriptomics company, addresses this problem by providing Spike-In RNA Variant Control Mixes (SIRVs) to the RNA-Seq community. These controls are processed together with the RNA sample to allow for an evaluation of the RNA-Seq workflow and, in particular, of transcript isoform detection and gene expression quantification. The mixes contain 69 transcript variants that map to 7 human model genes and mirror the native transcriptome complexity by comprehensively representing splicing isoforms, transcription start-site and end-site variants, overlapping transcripts and antisense transcription. Lukas Paul, Head of Services at Lexogen, describes in this webinar how the SIRVs have been used to estimate absolute accuracy and consistency, as well as concordance in gene expression measurements at the level of workflows, experiments, and samples. A “SIRVs dashboard” is introduced that brings together spike-in derived NGS data, annotations and data evaluation in an easily navigable way, and the webinar will highlight how condensed SIRVs data can function as a “RNA-Seq fingerprint” that enables comparisons across experiments, samples and platforms.

WEBINAR: Mapping nuclear-exosome targeted poly(A) tails with 3´-RNA seq

Kevin Roy

Postdoctoral Scholar, Department of Genetics, Stanford University

A large fraction of the RNA transcribed in eukaryotic cells is rapidly degraded in the nucleus. A poly-adenylation complex distinct from the canonical poly(A) machinery is responsible for initiating 3´-5´ degradation of nuclear RNAs. This non-canonical poly(A) machinery, termed the Trf4/5-Air1/2-Mtr4 or TRAMP complex, catalyzes the addition of 3-4 adenosines on target RNA 3´-ends. This tags the transcript for 3´-5´ exonuclease digestion by the nuclear RNA exosome, which can either degrade or trim the RNA in a manner dependent on the presence of RNA structures or RNA-binding proteins. Inactivating the nuclear exosome stabilizes these otherwise short-lived RNAs, and subsequent cellular polyadenylation lengthens the oligo(A) tails to >30 adenosines.The majority of these poly(A)+ 3´-ends arise from non-coding and pervasive RNA polymerase II (Pol II) transcripts undergoing transcription termination by the Nrd1-Nab3-Sen1 (NNS) complex. 3´-sequencing of RNAs from exosome-inactivated cells enabled mapping the precise 3´-ends of these unstable RNAs, providing a high-resolution view of NNS termination genome-wide.Surprisingly, different NNS-dependent terminators display substantial heterogeneity in the width of the termination window, with some genes terminating the majority of transcripts in a window of 500 bp. Further analysis of NNS-terminators with a narrow termination window revealed that a particular set of DNA-binding proteins cooperate with NNS by roadblocking Pol II to promote efficient transcription termination genome-wide. Using the QuantSeq 3´ mRNA-Seq library prep kits, we were able to multiplex >40 samples per sequencing lane and obtain between 2 to 5 million reads per sample. This enabled us to analyze numerous different strains with various exosome and roadblocking factors inactivated, showing that inactivating roadblocks shifted the window of NNS termination downstream. Strikingly, disabling NNS enabled elongation of Pol II through the same roadblocks.These results explain how RNA processing signals control the outcome of collisions between Pol II and DNA binding proteins.

WEBINAR: Gene Expression Analysis Using 3’-RNA Sequencing

Behnam Abasht, PhD

Assistant Professor, University of Delaware

RNA sequencing (RNA-seq) has revolutionized the study of gene expression in animals, plants and microorganisms. However, because of its high cost, this technology has been mainly used in experiments with limited number of samples. To examine a cost-effective alternative, we used a method, which confines sequencing to the 3’-end of mRNA and produces just one fragment per transcript, resulting in a dramatic decrease in sequencing cost. Total RNA isolated from chicken adipose tissue samples was used for cDNA library preparation using QuantSeq 3’mRNA-seq library Prep Kit. Sixty-one uniquely indexed cDNA libraries were pooled and sequenced on one lane on the Illumina Hiseq 2500. On average, 2.24 million reads per sample were generated, 90.1% of which were mapped to the chicken reference genome (Ensembl Galgal4). For more than 70% of the genes with detectable expression, we redefined the 3’-end and identified alternative polyadenylation sites within the 3’-untranslated regions. To compare gene expression measures between 3’-RNA-seq and RNA-seq technologies, we used data from a subset of 20 samples that were previously used in a RNA-seq study of feed efficiency. The correlation of the log10(fold-change) for gene expression (high- vs. low-feed efficiency birds) between these two methods was 0.90. In conclusion, 3’-RNA-seq is a cost effective method amenable to global gene expression studies at population-level, e.g., expression QTL (eQTL) mapping.  Also, it allows for accurate detection of the 3’-end of transcripts, enabling verification of the current gene model annotations and global characterization of alternative polyadenylation.