ABSTRACT
Adenosine to inosine (A-to-I) RNA editing, the most prevalent type of RNA editing in metazoans, is carried out by adenosine deaminases (ADARs) in double-stranded RNA regions. Several computational approaches have been recently developed to identify A-to-I RNA editing sites from sequencing data, each addressing a particular issue. Here, we present RNA Editing Sites Identification and Classification (RESIC), an efficient pipeline that combines several approaches for the detection and classification of RNA editing sites. The pipeline can be used for all organisms and can use any number of RNA-sequencing datasets as input. RESIC provides (1) the detection of editing sites in both repetitive and non-repetitive genomic regions; (2) the identification of hyper-edited regions; and (3) optional exclusion of polymorphism sites to increase reliability, based on DNA, and ADAR-mutant RNA sequencing datasets, or SNP databases. We demonstrate the utility of RESIC by applying it to human, successfully overlapping and extending the list of known putative editing sites. We further tested changes in the patterns of A-to-I RNA editing, and RNA abundance of ADAR enzymes, following SARS-CoV-2 infection in human cell lines. Our results suggest that upon SARS-CoV-2 infection, compared to mock, the number of hyper editing sites is increased, and in agreement, the activity of ADAR1, which catalyzes hyper-editing, is enhanced. These results imply the involvement of A-to-I RNA editing in conceiving the unpredicted phenotype of COVID-19 disease. RESIC code is open-source and is easily extendable.
ABSTRACT
Surveys among women with epilepsy (WWE) show that they receive their essential pregnancy-related information from many sources, including the internet. Our aim was to assess the types of websites provided by searching Google for the use of four antiepileptic drugs (AEDs) during pregnancy and lactation. The search was performed on 40 computers used by health-care professionals, on 40 computers used by nonhealth-care professionals, and on 5 computers used by WWE in Israel and on 8 computers used by nonhealth-care professionals in the U.S. On each computer, a Google search was conducted for term combinations that included one AED name ("carbamazepine","valproic acid", "lamotrigine", "levetiracetam", or "Keppra") and "Pregnancy", "Lactation", or "Breastfeeding". The top three and top ten websites retrieved in every search were mapped (a total of 45 and 150 websites, respectively, from each computer). Across all searches in English, on both U.S. and Israeli computers, the majority of websites listed among the first three and first ten results were those of independent health portals. The representation of the Epilepsy Foundation website was 10% or less, and only a few results were obtained from the NIH's general public-oriented MedlinePlus. In Hebrew, results included almost exclusively Israeli or Hebrew-translated websites. As in English, results from public-oriented, professionally-written websites in Hebrew accounted for less than 50% of entries. Overall, the availability of readable and high-quality information on AEDs used by pregnant and breastfeeding women is limited. Guiding patients towards accurate web resources can help them navigate among the huge amount of available online information.
