RNA editing is a post-transcriptional event that recodes hereditary information. Here we describe a comprehensive profile of the RNA editome of a male Han Chinese individual based on analysis of ∼ 767 million sequencing reads from poly(A)⁺, poly(A)⁻ and small RNA samples. We developed a computational pipeline that carefully controls for false positives while calling RNA editing events from genome and whole-transcriptome data of the same individual. We identified 22,688 RNA editing events in noncoding genes and introns, untranslated regions and coding sequences of protein-coding genes. Most changes ( ∼ 93%) converted A to I(G), consistent with known editing mechanisms based on adenosine deaminase acting on RNA (ADAR). We also found evidence of other types of nucleotide changes; however, these were validated at lower rates. We found 44 editing sites in microRNAs (miRNAs), suggesting a potential link between RNA editing and miRNA-mediated regulation. Our approach facilitates large-scale studies to profile and compare editomes across a wide range of samples.

Background: Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. Results: We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. Conclusions: We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

Hemoglobinopathies are among the most common autosomal-recessive disorders worldwide. A comprehensive next-generation sequencing (NGS) test would greatly facilitate screening and diagnosis of these disorders. An NGS panel targeting the coding regions of hemoglobin genes and four modifier genes was designed. We validated the assay by using 2522 subjects affected with hemoglobinopathies and applied it to carrier testing in a cohort of 10,111 couples who were also screened through traditional methods. In the clinical genotyping analysis of 1182 β-thalassemia subjects, we identified a group of additional variants that can be used for accurate diagnosis. In the molecular screening analysis of the 10,111 couples, we detected 4180 individuals in total who carried 4840 mutant alleles, and identified 186 couples at risk of having affected offspring. 12.1% of the pathogenic or likely pathogenic variants identified by our NGS assay, which were undetectable by traditional methods. Compared with the traditional methods, our assay identified an additional at-risk 35 couples. We describe a comprehensive NGS-based test that offers advantages over the traditional screening/molecular testing methods. To our knowledge, this is among the first large-scale population study to systematically evaluate the application of an NGS technique in carrier screening and molecular diagnosis of hemoglobinopathies.

Understanding of the RNA editing process has been broadened considerably by the next generation sequencing technology; however, several issues regarding this regulatory step remain unresolved – the strategies to accurately delineate the editome, the mechanism by which its profile is maintained, and its evolutionary and functional relevance. Here we report an accurate and quantitative profile of the RNA editome for rhesus macaque, a close relative of human. By combining genome and transcriptome sequencing of multiple tissues from the same animal, we identified 31,250 editing sites, of which 99.8% are A-to-G transitions. We verified 96.6% of editing sites in coding regions and 97.5% of randomly selected sites in non-coding regions, as well as the corresponding levels of editing by multiple independent means, demonstrating the feasibility of our experimental paradigm. Several lines of evidence supported the notion that the adenosine deamination is associated with the macaque editome – A-to-G editing sites were flanked by sequences with the attributes of ADAR substrates, and both the sequence context and the expression profile of ADARs are relevant factors in determining the quantitative variance of RNA editing across different sites and tissue types. In support of the functional relevance of some of these editing sites, substitution valley of decreased divergence was detected around the editing site, suggesting the evolutionary constraint in maintaining some of these editing substrates with their double-stranded structure. These findings thus complement the “continuous probing” model that postulates tinkering-based origination of a small proportion of functional editing sites. In conclusion, the macaque editome reported here highlights RNA editing as a widespread functional regulation in primate evolution, and provides an informative framework for further understanding RNA editing in human. RNA editing is a co-transcriptional process that introduces differences between RNA and its corresponding DNA sequence. Currently, the next generation sequencing have allowed study of the editome in a comprehensive and efficient manner. However, fundamental issues involving accurate mapping of the editome as well as its regulation and functional outcome remain unresolved. To further unveil the underlying mechanisms from the evolutionary perspective, we report here the editome profile in rhesus macaque, one of our closest evolutionary relatives. We identified a list of 31,250 RNA-editing sites and deciphered an accurate and informative editome across multiple tissues and animals. We found that the adenosine deamination is associated with the macaque editome, in that both the sequence context and the expression profile of ADARs are relevant factors in determining the quantitative variance of RNA editing across different sites and tissue types. Importantly, some of these RNA-editing events represent functional regulation, rather than neutral signals, as suggested by substitution valley of decreased divergence detected around the editing sites, an indication of selective constraint in maintaining some of these editing substrates with their double-stranded structure. The macaque editome thus provides an informative evolutionary context for an in-depth understanding of RNA editing regulation.