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RNA editing introduces single nucleotide changes to RNA, thus potentially diversifying gene expression. Recent studies have reported significant changes in RNA editing profiles in disease and development. The functional consequences of these widespread alterations remain elusive because of the unknown function of most RNA editing sites. Here, we carry out a comprehensive analysis of A-to-I editomes in human populations. Surprisingly, we observe highly similar editing profiles across populations despite striking differences in the expression levels of ADAR genes. Striving to explain this discrepancy, we uncover a functional mechanism of A-to-I editing in regulating mRNA abundance. We show that A-to-I editing stabilizes RNA secondary structures and reduces the accessibility of AGO2-miRNA to target sites in mRNAs. The editing-dependent stabilization of mRNAs in turn alters the observed editing levels in the stable RNA repertoire. Our study provides valuable insights into the functional impact of RNA editing in human cells. [ABSTRACT FROM AUTHOR]

Motivation: Accurate identification of genetic variants such as single-nucleotide polymorphisms (SNPs) or RNA editing sites from RNA-Seq reads is important, yet challenging, because it necessitates a very low false-positive rate in read mapping. Although many read aligners are available, no single aligner was specifically developed or tested as an effective tool for SNP and RNA editing prediction. Results: We present RASER, an accurate read aligner with novel mapping schemes and index tree structure that aims to reduce false-positive mappings due to existence of highly similar regions. We demonstrate that RASER shows the best mapping accuracy compared with other popular algorithms and highest sensitivity in identifying multiply mapped reads. As a result, RASER displays superb efficacy in unbiased mapping of the alternative alleles of SNPs and in identification of RNA editing sites. [ABSTRACT FROM AUTHOR]

Human saliva emerged as a research material in as early as the 17th century when investigators sought to understand the basis for salivary secretion (Garrett, 1975). Over the centuries, the focus of salivary research has evolved greatly and a wide range of topics has been examined (Garrett, 1975; Schipper et al., 2007). It is now known that the functions of saliva include at least lubrication, digestion of food, remineralization, prevention of demineralization, protection against microbial and viral infection, speech facilitation, and maintenance of oral and general health (Schipper et al., 2007; Malathi et al., 2014). One active research area related to human saliva is the discovery of biomarker molecules for a variety of diseases. Compared to other body fluids, saliva is easily accessible in a noninvasive manner. However, it is also immediately exposed to the outside environment, thus may be confounded by a wide variety of environmental factors. Nevertheless, previous studies have established that at least some human molecules in saliva are highly stable and potential biomarkers have been examined for a number of oral and systemic diseases (Bonne and Wong, 2012; Schafer et al., 2014). [ABSTRACT FROM AUTHOR]

Pre-mRNA splicing is regulated through the combinatorial activity of RNA motifs, including splice sites and splicing regulatory elements. Here we show that the activity of the G-run (polyguanine sequence) class of splicing enhancer elements is ∼4-fold higher when adjacent to intermediate strength 5′ splice sites (ss) than when adjacent to weak 5′ ss, and ∼1.3-fold higher relative to strong 5′ ss. We observed this dependence on 5′ ss strength in both splicing reporters and in global microarray and mRNA-Seq analyses of splicing changes following RNA interference against heterogeneous nuclear ribonucleoprotein (hnRNP) H, which cross-linked to G-runs adjacent to many regulated exons. An exon's responsiveness to changes in hnRNP H levels therefore depends in a complex way on G-run abundance and 5′ ss strength. This pattern of activity enables G-runs and hnRNP H to buffer the effects of 5′ ss mutations, augmenting both the frequency of 5′ ss polymorphism and the evolution of new splicing patterns. Certain other splicing factors may function similarly. [ABSTRACT FROM AUTHOR]

Accurate and efficient splicing of eukaryotic pre-mRNA5 requires recognition by transacting factors of a complex array of cis-acting RNA elements. Here, we developed a generalized Bayesian network to model the coevolution of splicing cis elements in diverse eukaryotic taxa. Cross-exon but not cross-intron compensatory interactions between the 5′ splice site (5'ss) and 3′ splice site (3'ss) were observed in human/mouse, indicating that the exon is the primary evolutionary unit in mammals. Studied plants, fungi, and invertebrates exhibited exclusively cross-intron interactions, suggesting that intron definition drives evolution in these organisms. In mammals, 5'ss strength and the strength of several classes of exonic splicing silencers (ESS5) evolved in a correlated way, whereas specific exonic splicing enhancers (ESEs), including motifs associated with hTra2, SRp55, and SRp20, evolved in a compensatory manner relative to the 5'ss and 3'ss. Interactions between specific ESS or ESE motifs were not observed, suggesting that elements bound by different factors are not commonly interchangeable. Thus, the splicing elements defining exons coevolve in a way that preserves overall exon strength, allowing specific elements to substitute for loss or weakening of others. [ABSTRACT FROM AUTHOR]

Sequence-specific recognition of nucleic-acid motifs is critical to many cellular processes. We have developed a new and general method called Neighborhood Inference (NI) that predicts sequences with activity in regulating a biochemical process based on the local density of known sites in sequence space. Applied to the problem of RNA splicing regulation, NI was used to predict hundreds of new exonic splicing enhancer (ESE) and silencer (ESS) hexanucleotides from known human ESEs and ESSs. These predictions were supported by cross-validation analysis, by analysis of published splicing regulatory activity data, by sequence-conservation analysis, and by measurement of the splicing regulatory activity of 24 novel predicted ESEs, ESSs, and neutral sequences using an in vivo splicing reporter assay. These results demonstrate the ability of NI to accurately predict splicing regulatory activity and show that the scope of exonic splicing regulatory elements is substantially larger than previously anticipated. Analysis of orthologous exons in four mammals showed that the NI score of ESEs, a measure of function, is much more highly conserved above background than ESE primary sequence. This observation indicates a high degree of selection for ESE activity in mammalian exons, with surprisingly frequent interchangeability between ESE sequences. INSET: Synopsis. [ABSTRACT FROM AUTHOR]

We introduce a system identification method based on weighted-principal component regression (WPCR). This approach aims to identify the dynamics in a linear time-invariant (LTI) model which may represent a resting physiologic system. It tackles the time-domain system identification problem by considering, asymptotically, frequency information inherent in the given data. By including in the model only dominant frequency components of the input signal(s), this method enables construction of candidate models that are specific to the data and facilitates a reduction in parameter estimation error when the signals are colored (as are most physiologic signals). Additionally, this method allows incorporation of preknowledge about the system through a weighting scheme. We present the method in the context of single-input and multi-input single-output systems operating in open-loop and closed-loop. In each scenario, we compare the WPCR method with conventional approaches and approaches that also build data-specific candidate models. Through both simulated and experimental data, we show that the WPCR method enables more accurate identification of the system impulse response function than the other methods when the input signal(s) is colored. [ABSTRACT FROM AUTHOR]

Background: There are numerous anecdotal reports of ventricular arrhythmias during spaceflight; however, it is not known whether spaceflight or microgravity systematically increases the risk of cardiac dysrhythmias. Microvolt T wave alternans (MTWA) testing compares favorably with other noninvasive risk stratifiers and invasive electrophysiological testing in patients as a predictor of sudden cardiac death, ventricular tachycardia, and ventricular fibrillation. We hypothesized that simulated microgravity leads to an increase in MTWA. Methods: Twenty-four healthy male subjects underwent 9 to 16 days of head-down tilt bed rest (HDTB). MTWA was measured before and after the bed rest period during bicycle exercise stress. For the purposes of this study, we defined MTWA outcome to be positive if sustained MTWA was present with an onset heart rate ≤125 bpm. During various phases of HDTB, the following were also performed: daily 24-hour urine collections, serum electrolytes and catecholamines, and cardiovascular system identification (measure of autonomic function). Results: Before HDTB, 17% of the subjects were MTWA positive [95%CI: (0.6%, 37%)]; after HDTB, 42% of the subjects were MTWA positive [95%CI: (23%, 63%)] (P = 0.03). The subjects who were MTWA positive after HDTB compared with MTWA negative subjects had an increased versus decreased sympathetic responsiveness (P = 0.03) and serum norepinephrine levels (P = 0.05), and a trend toward higher potassium excretion (P = 0.06) after bed rest compared to baseline. Conclusions: HDTB leads to an increase in MTWA, providing the first evidence that simulated microgravity has a measurable effect on electrical repolarization processes. Possible contributing factors include loss in potassium and changes in sympathetic function. A.N.E. 2005;10(3):363–370 [ABSTRACT FROM AUTHOR]

We introduce a model order selection criterion called signal prediction error (SPE) for the identification of a linear regression model, which can be an adequate representation of a resting physiologic system. SPE is an estimate of the prediction error variance due only to model estimation error and not unobserved noise, which distinguishes it from the widely used final prediction error (FPE). We then present a theoretical analysis of SPE, which predicts that its ability to select correctly the model order is more dependent on the signal-to-noise ratio (SNR) and less dependent on the number of data samples available for analysis. We next propose a heuristic procedure based on SPE (called SPED) to improve its robustness to SNR levels. We then demonstrate, through simulated physiologic data at high SNR levels, that SPE will be equivalent to consistent model order selection criteria for long data records but will become superior to FPE and other model order selection criteria as the size of the data record decreases. The simulated data results also show that SPED is indeed a significant improvement over SPE in terms of robustness to SNR. Finally; we demonstrate the applicability of SPE and SPED to actual cardio-respiratory-renal data. [ABSTRACT FROM AUTHOR]

A long-term goal of our research is to understand the RNA splicing code: how exons and splice sites are identified in primary transcripts, and how this code is altered in cell- and condition-specific alternative splicing. We are focusing on understanding the context-dependent activities and interactions among splicing regulatory elements. We have found that most members of a class of elements known as exonic splicing silencers share a consistent pattern of context-dependent activity, silencing splicing when present in exons, activating splicing when present in introns, and altering splice site choice when present between competing splice sites. Splicing regulatory activity may also depend on splice site strength; we are exploring a pattern in which some intronic splicing enhancers enhance splicing of exons more strongly when 5' splice site (5'ss) strength is weak/moderate than when the 5'ss is either stronger or weaker. We are also using computational approaches to identify pairs of preferentially co-occurring motifs, and have used this approach to identify a pair of intronic motifs that can function cooperatively to silence the splicing of intervening exons. [ABSTRACT FROM AUTHOR]