Assessment of two-pool multiplex long-amplicon nanopore sequencing of SARS-CoV-2.

Genomic surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays an important role in COVID-19 pandemic control and elimination efforts, especially by elucidating its global transmission network and illustrating its viral evolution. The deployment of multiplex PCR assays that target SARS-CoV-2 followed by either massively parallel or nanopore sequencing is a widely-used strategy to obtain genome sequences from primary samples. However, multiplex PCR-based sequencing carries an inherent bias of sequencing depth among different amplicons, which may cause uneven coverage. Here we developed a two-pool, long-amplicon 36-plex PCR primer panel with ~1000-bp amplicon lengths for full-genome sequencing of SARS-CoV-2. We validated the panel by assessing nasopharyngeal swab samples with a <30 quantitative reverse transcription PCR cycle threshold value and found that ≥90% of viral genomes could be covered with high sequencing depths (≥20% mean depth). In comparison, the widely-used ARTIC panel yielded 79%-88% high-depth genome regions. We estimated that ~5 Mbp nanopore sequencing data may ensure a >95% viral genome coverage with a ≥10-fold depth and may generate reliable genomes at consensus sequence levels. Nanopore sequencing yielded false-positive variations with frequencies of supporting reads <0.8, and the sequencing errors mostly occurred on the 5' or 3' ends of reads. Thus, nanopore sequencing could not elucidate intra-host viral diversity.

Systematic Identification and Assessment of Therapeutic Targets for Breast Cancer Based on Genome-Wide RNA Interference Transcriptomes.

With accumulating public omics data, great efforts have been made to characterize the genetic heterogeneity of breast cancer. However, identifying novel targets and selecting the best from the sizeable lists of candidate targets is still a key challenge for targeted therapy, largely owing to the lack of economical, efficient and systematic discovery and assessment to prioritize potential therapeutic targets. Here, we describe an approach that combines the computational evaluation and objective, multifaceted assessment to systematically identify and prioritize targets for biological validation and therapeutic exploration. We first establish the reference gene expression profiles from breast cancer cell line MCF7 upon genome-wide RNA interference (RNAi) of a total of 3689 genes, and the breast cancer query signatures using RNA-seq data generated from tissue samples of clinical breast cancer patients in the Cancer Genome Atlas (TCGA). Based on gene set enrichment analysis, we identified a set of 510 genes that when knocked down could significantly reverse the transcriptome of breast cancer state. We then perform multifaceted assessment to analyze the gene set to prioritize potential targets for gene therapy. We also propose drug repurposing opportunities and identify potentially druggable proteins that have been poorly explored with regard to the discovery of small-molecule modulators. Finally, we obtained a small list of candidate therapeutic targets for four major breast cancer subtypes, i.e., luminal A, luminal B, HER2+ and triple negative breast cancer. This RNAi transcriptome-based approach can be a helpful paradigm for relevant researches to identify and prioritize candidate targets for experimental validation.

In silico genetic robustness analysis of secondary structural elements in the miRNA gene.

Genetic robustness, insensitivity of the phenotype facing genetic mutations, is a fundamental and ubiquitously observed property of biological systems. In this study, we investigate the genetic robustness of the structural elements within native miRNA genes on a genome-wide scale. MicroRNAs (miRNAs) are a large family of endogenous noncoding RNAs that regulate gene expression at the posttranscriptional level. We examine the neutrality of the structural element in 1082 native pre-miRNAs from six species and demonstrate that the structural elements in native pre-miRNAs exhibit a significantly higher level of genetic robustness in comparison with structural elements within random pseudo pre-miRNAs. Hence, this excess robustness of structural elements in pre-miRNAs goes beyond the intrinsic robustness of the stem-loop structure. Furthermore, we show that it is not a by-product of a base composition bias. Interestingly, our data also demonstrate a difference in increased levels of average neutrality between structural elements. Remarkably, differential genetic robustness between structural elements is observed in both native and pseudo pre-miRNAs. Our results are much in agreement with previous experimental observations, and suggest that the genetic robustness of secondary structural elements in native pre-miRNAs, under different evolutionary selection pressures, may evolve due to its own selective advantage.

RSRE: RNA structural robustness evaluator.

Biological robustness, defined as the ability to maintain stable functioning in the face of various perturbations, is an important and fundamental topic in current biology, and has become a focus of numerous studies in recent years. Although structural robustness has been explored in several types of RNA molecules, the origins of robustness are still controversial. Computational analysis results are needed to make up for the lack of evidence of robustness in natural biological systems. The RNA structural robustness evaluator (RSRE) web server presented here provides a freely available online tool to quantitatively evaluate the structural robustness of RNA based on the widely accepted definition of neutrality. Several classical structure comparison methods are employed; five randomization methods are implemented to generate control sequences; sub-optimal predicted structures can be optionally utilized to mitigate the uncertainty of secondary structure prediction. With a user-friendly interface, the web application is easy to use. Intuitive illustrations are provided along with the original computational results to facilitate analysis. The RSRE will be helpful in the wide exploration of RNA structural robustness and will catalyze our understanding of RNA evolution. The RSRE web server is freely available at http://biosrv1.bmi.ac.cn/RSRE/ or http://biotech.bmi.ac.cn/RSRE/.