Daniela Munafo

Selective Depletion of Abundant RNAs to Enable Transcriptome Analysis of Low‐Input and Highly Degraded Human RNA

Ribosomal RNAs (rRNAs) are extremely abundant, often constituting 80% to 90% of total RNA. Since rRNA sequences are often not of interest in genomic RNA sequencing experiments, rRNAs can be removed from the sample before the library preparation step, in order to prevent the majority of the library and the majority of sequencing reads from being rRNA. Removal of rRNA can be especially challenging for low quality and formalin‐fixed paraffin‐embedded (FFPE) RNA samples due to the fragmented nature of these RNA molecules. The NEBNext rRNA Depletion Kit (Human/Mouse/Rat) depletes both cytoplasmic (5 S rRNA, 5.8 S rRNA, 18 S rRNA, and 28 S rRNA) and mitochondrial rRNA (12 S rRNA and 16 S rRNA) from total RNA preparations from human, mouse, and rat samples. Due to the high similarity among mammalian rRNA sequences, it is likely that rRNA depletion can also be achieved for other mammals but has not been empirically tested. This product is compatible with both intact and degraded RNA (e.g., FFPE RNA). The resulting rRNA‐depleted RNA is suitable for RNA‐seq, random‐primed cDNA synthesis, or other downstream RNA analysis applications. Regardless of the quality or amount of input RNA, this method efficiently removes rRNA, while retaining non‐coding and other non‐poly(A) RNAs. The NEBNext rRNA Depletion Kit thus provides a more complete picture of the transcript repertoire than oligo d(T) poly(A) mRNA enrichment methods.

Abstract 3186: Comparative analysis of different total RNA sequencing approaches

Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL Initial transcriptomic studies largely relied on hybridization-based microarray technologies and offered a limited ability to fully catalogue and quantify the diverse RNA molecules that are expressed from genomes over wide ranges of levels. Massively parallel cDNA sequencing, or Total RNA-Seq, has allowed many advances in the characterization and quantification of transcriptomes; an offer a new appreciation for the complexity of the Transcriptome, encompassing a multitude of previously unknown coding and non-coding RNA species, particularly small RNAs, including micro RNAs. This work investigates the performance of different strategies for Total RNA-Seq using multiple next generation sequencing platforms. Standard RNA-sequencing approaches generally require double-stranded cDNA Synthesis, which erases RNA strand information. Synthesis of a randomly primed double-stranded cDNA followed by addition of adaptors for next-generation sequencing leads to the loss of information about which strand was present in the original mRNA template. The polarity of the transcript is important for correct annotation of novel genes, identification of antisense transcripts with potential regulatory roles, and for correct determination of gene expression levels in the presence of antisense transcripts. Here, we examine the performance of strand-specific RNA libraries made by direct ligation of adaptor on to the RNA. We analyze the effect of different RNA fragmentation methods (divalent cations plus heat versus enzymatic fragmentation) and we provide a comparative data analysis (library complexity, continuity of gene coverage, strand specificity and 3′and 5′-end bias analysis). Identification and analysis of small RNA by deep sequencing requires preparation of a di-tagged cDNA library, which leads to adaptor-dimer formation that strongly contaminates the library. We have developed a novel method to generate di-tagged small RNA libraries free of adapter-dimer contamination without introducing any additional enzymatic steps or gel purifications. This method has optimized the 3′adaptor-ligation reaction to recover and to increase representation of the 2′-O-modified RNAs present in a biological sample. To reduce cost and increase sample throughput we have developed a barcode strategy to tag samples during library construction. The multiplexed libraries can then be pooled together before size selection, reducing the number of steps in the workflow. This technique reduces bias by ligation, increases representation of modified small RNAs and simplifies workflow during library construction for small RNA analysis and discovery. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3186. doi:1538-7445.AM2012-3186

A fast solution to NGS library preparation with low nanogram DNA input.

Next-generation sequencing (NGS) has significantly impacted human genetics, enabling a comprehensive characterization of human genome as well as better understanding of many genomic abnormalities. By delivering massive DNA sequences at unprecedented speed and cost, NGS promises to make personalized medicine a reality in the foreseeable future. To date, library construction with clinical samples has been a challenge, primarily due to the limited quantities of sample DNA available. To overcome this challenge, we have developed a fast library preparation method using novel NEBNext reagents and adaptors, including a new DNA polymerase that has been optimized to minimize GC bias. This method enables library construction from an amount of DNA as low as 5 ng, and can be used for both intact and fragmented DNA. Moreover, the workflow is compatible with multiple NGS platforms.

Comparative analysis of strand-specific RNA sequencing approaches

Background Standard RNA sequencing approaches generally require double-stranded cDNA synthesis, which erases RNA strand information. Synthesis of a randomly primed double-stranded cDNA followed by addition of adaptors for next-generation sequencing leads to the loss of information about which strand was present in the original mRNA template. The polarity of the transcript is important for correct annotation of novel genes, identification of antisense transcripts with potential regulatory roles, and for correct determination of gene expression levels in the presence of antisense transcripts. Different strand-specific RNA-seq approaches have been developed to preserve information about strand polarity with different level of performances. Material and methods Using Illumina Deep Sequencing Technology, this work investigates the performance of two different directional RNA-Seq (strand-specific RNA-seq) strategies. One is based on direct ligation of adaptors to the RNA ends and the other is based on the labeling and excision of the second strand cDNA. The RNA-seq workflows present in this work have been improved over current more laborious RNA-seq methods. Their low RNA input and streamlined workflows make them compatible with high throughput and automation. We also analyze the effect of different RNA fragmentation methods (divalent cations plus heat versus enzymatic fragmentation). Results We will provide a comparative full data analysis of different strand-specific RNA methods (library performance, complexity, continuity of gene coverage, strand specificity, rRNA background). Conclusions Our results show improved methods for high-quality strand-specific RNA-seq library construction amenable to large-scale library construction and automation.