Characterizing SARS-CoV-2 Genomes from Patient Samples Using Total RNA-Seq
Italian scientists sequenced four SARS-CoV-2 genome samples from cases epidemiologically linked to Nothern Italy using the Zymo-Seq RiboFree Total RNA Library Kit.
Sequence analysis showed good coverage along the SARS-CoV-2 genome for all four isolates. The researchers used these data to phylogenetically group the new isolates with previously characterized patient samples.
These findings suggest RNA-Seq is a powerful tool, combined with epidemiological data, to help us comprehensively study the COVID-19 pandemic. Discover how the RiboFree Universal Depletion technology simplifies RNA-Seq and maximizes relevant sequencing reads.
Save Over 6 Hours – The Easiest Kit For Library Prep
Zymo-Seq RiboFree Total RNA Library Kit minimizes the number of reagents and steps needed to generate stranded, rRNA-depleted total RNA-Seq libraries.
Probe-free rRNA Depletion – Compatible With Any Organism
RiboFree depletion will remove rRNA from any sample type. Paired-end sequencing was performed on stranded total RNA-Seq libraries containing ERCC Spike-In Mix 1 (Life Technologies), both with and without RiboFree depletion. Read pairs were aligned to their respective genomes using the STAR aligner. Read classes were defined using a combination of Ensembl GTF gene biotypes and RepBase repeat masker annotations. Number of reads overlapping each annotation class were divided by total reads in that library to calculate percent reads of each annotation class.
35x Less Biased Expression Profiles – Eliminate Off-Target Ribo‑Depletion
The novel probe-free technology utilized in the Zymo-Seq RiboFree Total RNA Library Kit dramatically decreases genes affected by rRNA removal (Ribo-ZeroTM Gold probe-based depletion) or mRNA enrichment (Universal Plus poly(A) pulldown).
Probe-free. Bias‑free. RiboFree. – The Most Accurate rRNA Depletion
RiboFree depletion maintains native expression profiles unlike Supplier i [probe-based Ribo-ZeroTM Gold] and Supplier NG [poly(A) enrichment]. Paired-end sequencing was performed on libraries prepared from Universal Human Reference RNA (Invitrogen) containing ERCC Spike-In Mix 1 (Life Technologies), both with and without rRNA removal. Libraries were sequenced to a depth of ∼35 million reads per library, and read pairs were aligned to the hg38 human genome using the STAR aligner. The DESeq2 package was used to apply “apeglm” as a log-fold-change shrinkage correlation and to determine which of the 20,004 protein coding genes and ERCC Spike-In transcripts were significantly affected (p.adj < 0.05) by rRNA removal. Significantly affected transcripts are represented as colored dots in the scatterplots.