RNA editing is a process that modifies RNA nucleotides and changes the efficiency and fidelity of the central dogma. Enzymes that catalyze RNA editing are required for life, and defects in RNA editing are associated with many diseases. Recent advances in sequencing have enabled the genome-wide identification of RNA editing sites in mammalian transcriptomes. Here, we demonstrate that canonical RNA editing (A-to-I and C-to-U) occurs in liver, white adipose, and bone tissues of the laboratory mouse, and we show that apparent non-canonical editing (all other possible base substitutions) is an artifact of current high-throughput sequencing technology. Further, we report that high-confidence canonical RNA editing sites can cause non-synonymous amino acid changes and are significantly enriched in 3′ UTRs, specifically at microRNA target sites, suggesting both regulatory and functional consequences for RNA editing.

MicroRNAs (miRNAs) are approximately 22 nucleotide (nt) long and play important roles in post-transcriptional regulation in both plants and animals. In animals, precursor (pre-) miRNAs are ∼70 nt hairpins produced by Drosha cleavage of long primary (pri-) miRNAs in the nucleus. Exportin-5 (XPO5) transports pre-miRNAs into the cytoplasm for Dicer processing. Alternatively, pre-miRNAs containing a 5′ 7-methylguanine (m7G-) cap can be generated independently of Drosha and XPO5. Here we identify a class of m7G-capped pre-miRNAs with 5′ extensions up to 39 nt long. The 5′-extended pre-miRNAs are transported by Exportin-1 (XPO1). Unexpectedly, a long 5′ extension does not block Dicer processing. Rather, Dicer directly cleaves 5′-extended pre-miRNAs by recognizing its 3′ end to produce mature 3p miRNA and extended 5p miRNA both in vivo and in vitro. The recognition of 5′-extended pre-miRNAs by the Dicer Platform-PAZ-Connector (PPC) domain can be traced back to ancestral animal Dicers, suggesting that this previously unrecognized Dicer reaction mode is evolutionarily conserved. Our work reveals additional genetic sources for small regulatory RNAs and substantiates Dicer's essential role in RNAi-based gene regulation.

The Streptococcus mutans Cid/Lrg system is central to the physiology of this cariogenic organism, affecting oxidative stress resistance, biofilm formation and competence. Previous transcriptome analyses of lytS (responsible for the regulation of lrgAB expression) and cidB mutants have revealed pleiotropic effects on carbohydrate metabolism and stress resistance genes. In this study, it was found that an lrgAB mutant, previously shown to have diminished aerobic and oxidative stress growth, was also much more growth impaired in the presence of heat and vancomycin stresses, relative to wild-type, lrgA and lrgB mutants. To obtain a more holistic picture of LrgAB and its involvement in stress resistance, RNA sequencing and bioinformatics analyses were used to assess the transcriptional response of wild-type and isogenic lrgAB mutants under anaerobic (control) and stress-inducing culture conditions (aerobic, heat and vancomycin). Hierarchical clustering and principal components analyses of all differentially expressed genes revealed that the most distinct gene expression profiles between S. mutans UA159 and lrgAB mutant occurred during aerobic and high-temperature growth. Similar to previous studies of a cidB mutant, lrgAB stress transcriptomes were characterized by a variety of gene expression changes related to genomic islands, CRISPR-C as systems, ABC transporters, competence, bacteriocins, glucosyltransferases, protein translation, tricarboxylic acid cycle, carbohydrate metabolism/storage and transport. Notably, expression of lrgAB was upregulated in the wild-type strain under all three stress conditions. Collectively, these results demonstrate that mutation of lrgAB alters the transcriptional response to stress, and further support the idea that the Cid/Lrg system acts to promote cell homeostasis in the face of environmental stress.

MicroRNAs (miRNAs) are a class of endogenous, non-coding RNAs that mediate post-transcriptional gene silencing by inhibiting mRNA translation and promoting mRNA decay. DICER1, an RNase III endonuclease encoded by Dicer1, is required for processing short 21–22 nucleotide miRNAs from longer double-stranded RNA precursors. Here, we investigate the loss of Dicer1 in mouse postnatal male germ cells to determine how disruptions in the miRNA biogenesis pathway may contribute to infertility. Reduced levels of Dicer1 transcripts and DICER1 were confirmed in germ cell knock-out (GCKO) testes by postnatal day 18 (P18). Compared to wild-type (WT) at 8 weeks, GCKO males had no change in body weight; yet showed significant reductions in testis mass and sperm number. Histology and fertility tests confirmed spermatogenic failure in GCKO males. Array analyses at P18 showed that in comparison to WT testes, 75% of miRNA genes and 37% of protein coding genes were differentially expressed in GCKO testes. Among these, 96% of miRNA genes were significantly down-regulated, while 4% miRNA genes were overexpressed. Interestingly, we observed preferential overexpression of genes encoded on the sex chromosomes in GCKO testes, including more than 80% of previously identified targets of meiotic sex chromosome inactivation (MSCI). Compared to WT, GCKO mice showed higher percentages of germ cells at early meiotic stages (leptotene and zygotene) but lower percentages at later stages (pachytene, diplotene and metaphase I) providing evidence that deletion of Dicer1 leads to disruptions in meiotic progression. Therefore, deleting Dicer1 in early postnatal germ cells resulted in deregulation of transcripts encoded by genes on the sex chromosomes, impaired meiotic progression and led to spermatogenic failure and infertility.

RNA editing refers to post-transcriptional processes that alter the base sequence of RNA. Recently, hundreds of new RNA editing targets have been reported. However, the mechanisms that determine the specificity and degree of editing are not well understood. We examined quantitative variation of site-specific editing in a genetically diverse multiparent population, Diversity Outbred mice, and mapped polymorphic loci that alter editing ratios globally for C-to-U editing and at specific sites for A-to-I editing. An allelic series in the C-to-U editing enzyme Apobec1 influences the editing efficiency of Apob and 58 additional C-to-U editing targets. We identified 49 A-to-I editing sites with polymorphisms in the edited transcript that alter editing efficiency. In contrast to the shared genetic control of C-to-U editing, most of the variable A-to-I editing sites were determined by local nucleotide polymorphisms in proximity to the editing site in the RNA secondary structure. Our results indicate that RNA editing is a quantitative trait subject to genetic variation and that evolutionary constraints have given rise to distinct genetic architectures in the two canonical types of RNA editing.KEYWORDS genetics; RNA editing; Diversity Outbred; Apobec1; secondary structure; Multiparent Advanced Generation Inter-Cross (MAGIC); multiparental populations; MPP R NA EDITING in mammals occurs through deamination of adenosine, which is converted to inosine (A-to-I editing), or deamination of cytosine, which is converted to uracil (C-to-U editing) (Davidson and Shelness 2000;Bass 2002). Other types of editing have been reported, but these findings remain controversial (Bass et al. 2012;Gu et al. 2012). The two canonical editing types, A-to-I and C-to-U editing, are mediated by distinct pathways. A-to-I editing is catalyzed on double-stranded (ds) RNA by proteins in the adenosine deaminase, RNA-specific (ADAR) family (ADAR1 and ADAR2) and is most common in neuronal tissues. However, the Adar gene family is ubiquitously expressed, and editing has been reported in many other tissues (Gu et al. 2012).Homozygous deletion of Adar genes is embryonic lethal in mice, and defects in A-to-I editing have been associated with neurodegenerative disorders and cancers (Gurevich et al. 2002;Paz et al. 2007). The C-to-U editing pathway is catalyzed by apolipoprotein B messenger RNA (mRNA) editing enzyme catalytic polypeptide 1 (Apobec1), which is expressed primarily in small intestine and liver, where it targets the transcript of apolipoprotein B (Apob), converting a CAA (glutamine) codon within the coding sequence to a stop codon (UAA). This editing event results in two APOB protein isoforms, APOB48 from the edited transcript and APOB100 from the unedited transcript. Editing of Apob is evolutionarily conserved and occurs in mice, humans, and other mammals. The edited isoform APOB48 functions in the synthesis, assembly, and secretion of chylomicrons in the small intestine; the unedited isoform APOB100 is expressed in the liver and gives ris...

Acute airway acidification is a potent stimulus of sensory nerves and occurs commonly with gastroesophageal reflux disease, cystic fibrosis, and asthma. In infants and adults, airway acidification can acutely precipitate asthma-like symptoms, and treatment-resistant asthma can be associated with gastroesophageal reflux disease. Airway protective behaviors, such as mucus secretion and airway smooth muscle contraction, are often exaggerated in asthma. These behaviors are manifested through activation of neural circuits. In some populations, the neural response to acid might be particularly important. For example, the immune response in infants is relatively immature compared with adults. Infants also have a high frequency of gastroesophageal reflux. Thus, in the current study, we compared the transcriptomes of an airway-nervous system circuit (e.g., tracheal epithelia, nodose ganglia, and brain stem) in neonatal piglets challenged with intra-airway acid. We hypothesized that the identification of parallel changes in the transcriptomes of two neutrally connected tissues might reveal the circuit response, and, hence, molecules important for the manifestation of asthma-like features. Intra-airway acid induced airway hyperreactivity and airway obstruction in male piglets. In contrast, female piglets displayed airway obstruction without airway hyperreactivity. Pairwise comparisons revealed parallel changes in genes directly implicated in airway hyperreactivity ( scn10a) in male acid-challenged piglets, whereas acid-challenged females exhibited parallel changes in genes associated with mild asthma ( stat 1 and isg15). These findings reveal sex-specific responses to acute airway acidification and highlight distinct molecules within a neural circuit that might be critical for the manifestation of asthma-like symptoms in pediatric populations.

Despite considerable progress understanding genes that affect the HDL particle, its function, and cholesterol content, genes identified to date explain only a small percentage of the genetic variation. We used N-ethyl-N-nitrosourea mutagenesis in mice to discover novel genes that affect HDL cholesterol levels. Two mutant lines (Hlb218 and Hlb320) with low HDL cholesterol levels were established. Causal mutations in these lines were mapped using linkage analysis: for line Hlb218 within a 12 Mbp region on Chr 10; and for line Hlb320 within a 21 Mbp region on Chr 7. High-throughput sequencing of Hlb218 liver RNA identified a mutation in Pla2g12b. The transition of G to A leads to a cysteine to tyrosine change and most likely causes a loss of a disulfide bridge. Microarray analysis of Hlb320 liver RNA showed a 7-fold downregulation of Hpn; sequencing identified a mutation in the 3′ splice site of exon 8. Northern blot confirmed lower mRNA expression level in Hlb320 and did not show a difference in splicing, suggesting that the mutation only affects the splicing rate. In addition to affecting HDL cholesterol, the mutated genes also lead to reduction in serum non-HDL cholesterol and triglyceride levels. Despite low HDL cholesterol levels, the mice from both mutant lines show similar atherosclerotic lesion sizes compared to control mice. These new mutant mouse models are valuable tools to further study the role of these genes, their affect on HDL cholesterol levels, and metabolism.

Background microRNAs (miRNAs) have been shown to play essential roles in a wide range of biological processes. Many computational methods have been developed to identify targets of miRNAs. However, the majority of these methods depend on pre-defined features that require considerable efforts and resources to compute and often prove suboptimal at predicting miRNA targets. Results We developed a novel hybrid deep learning-based (DL-based) approach that is capable of predicting miRNA targets at a higher accuracy. This approach integrates convolutional neural networks (CNNs) that excel in learning spatial features and recurrent neural networks (RNNs) that discern sequential features. Therefore, our approach has the advantages of learning both the intrinsic spatial and sequential features of miRNA:target. The inputs for our approach are raw sequences of miRNAs and genes that can be obtained effortlessly. We applied our approach on two human datasets from recently miRNA target prediction studies and trained two models. We demonstrated that the two models consistently outperform the previous methods according to evaluation metrics on test datasets. Comparing our approach with currently available alternatives on independent datasets shows that our approach delivers substantial improvements in performance. We also show with multiple evidences that our approach is more robust than other methods on small datasets. Our study is the first study to perform comparisons across multiple existing DL-based approaches on miRNA target prediction. Furthermore, we examined the contribution of a Max pooling layer in between the CNN and RNN and demonstrated that it improves the performance of all our models. Finally, a unified model was developed that is robust on fitting different input datasets. Conclusions We present a new DL-based approach for predicting miRNA targets and demonstrate that our approach outperforms the current alternatives. We supplied an easy-to-use tool, miTAR, at https://github.com/tjgu/miTAR. Furthermore, our analysis results support that Max Pooling generally benefits the hybrid models and potentially prevents overfitting for hybrid models.