69 research outputs found

    Discovery of new genes and deletion editing in Physarum mitochondria enabled by a novel algorithm for finding edited mRNAs

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    Gene finding is complicated in organisms that exhibit insertional RNA editing. Here, we demonstrate how our new algorithm Predictor of Insertional Editing (PIE) can be used to locate genes whose mRNAs are subjected to multiple frameshifting events, and extend the algorithm to include probabilistic predictions for sites of nucleotide insertion; this feature is particularly useful when designing primers for sequencing edited RNAs. Applying this algorithm, we successfully identified the nad2, nad4L, nad6 and atp8 genes within the mitochondrial genome of Physarum polycephalum, which had gone undetected by existing programs. Characterization of their mRNA products led to the unanticipated discovery of nucleotide deletion editing in Physarum. The deletion event, which results in the removal of three adjacent A residues, was confirmed by primer extension sequencing of total RNA. This finding is remarkable in that it comprises the first known instance of nucleotide deletion in this organelle, to be contrasted with nearly 500 sites of single and dinucleotide addition in characterized mitochondrial RNAs. Statistical analysis of this larger pool of editing sites indicates that there are significant biases in the 2 nt immediately upstream of editing sites, including a reduced incidence of nucleotide repeats, in addition to the previously identified purine-U bias

    Analytical approaches to detect maternal/fetal genotype incompatibilities that increase risk of pre-eclampsia

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    <p>Abstract</p> <p>Background</p> <p>In utero interactions between incompatible maternal and fetal genotypes are a potential mechanism for the onset or progression of pregnancy related diseases such as pre-eclampsia (PE). However, the optimal analytical approach and study design for evaluating incompatible maternal/offspring genotype combinations is unclear.</p> <p>Methods</p> <p>Using simulation, we estimated the type I error and power of incompatible maternal/offspring genotype models for two analytical approaches: logistic regression used with case-control mother/offspring pairs and the log-linear regression used with case-parent triads. We evaluated a real dataset consisting of maternal/offspring pairs with and without PE for incompatibility effects using the optimal analysis based on the results of the simulation study.</p> <p>Results</p> <p>We identified a single coding scheme for the incompatibility effect that was equally or more powerful than all of the alternative analysis models evaluated, regardless of the true underlying model for the incompatibility effect. In addition, the log-linear regression was more powerful than the logistic regression when the heritability was low, and more robust to adjustment for maternal or fetal effects. For the PE data, this analysis revealed three genes, lymphotoxin alpha (<it>LTA</it>), von Willebrand factor (<it>VWF</it>), and alpha 2 chain of type IV collagen (<it>COL4A2</it>) with possible incompatibility effects.</p> <p>Conclusion</p> <p>The incompatibility model should be evaluated for complications of pregnancy, such as PE, where the genotypes of two individuals may contribute to the presence of disease.</p

    Postmenopausal hormones and sleep quality in the elderly: a population based study

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    <p>Abstract</p> <p>Background</p> <p>Sleep disturbance and insomnia are commonly reported by postmenopausal women. However, the relationship between hormone therapy (HT) and sleep disturbances in postmenopausal community-dwelling adults is understudied. Using data from the multicenter Study of Osteoporotic Fractures (SOF), we tested the relationship between HT and sleep-wake estimated from actigraphy.</p> <p>Methods</p> <p>Sleep-wake was ascertained by wrist actigraphy in 3,123 women aged 84 ± 4 years (range 77-99) from the Study of Osteoporotic Fractures (SOF). This sample represents 30% of the original SOF study and 64% of participants seen at this visit. Data were collected for a mean of 4 consecutive 24-hour periods. Sleep parameters measured objectively included total sleep time, sleep efficiency (SE), sleep latency, wake after sleep onset (WASO), and nap time. All analyses were adjusted for potential confounders (age, clinic site, race, BMI, cognitive function, physical activity, depression, anxiety, education, marital status, age at menopause, alcohol use, prior hysterectomy, and medical conditions).</p> <p>Results</p> <p>Actigraphy measurements were available for 424 current, 1,289 past, and 1,410 never users of HT. Women currently using HT had a shorter WASO time (76 vs. 82 minutes, P = 0.03) and fewer long-wake (≥ 5 minutes) episodes (6.5 vs. 7.1, P = 0.004) than never users. Past HT users had longer total sleep time than never users (413 vs. 403 minutes, P = 0.002). Women who never used HT had elevated odds of SE <70% (OR,1.37;95%CI,0.98-1.92) and significantly higher odds of WASO ≥ 90 minutes (OR,1.37;95%CI,1.02-1.83) and ≥ 8 long-wake episodes (OR,1.58;95%CI,1.18-2.12) when compared to current HT users.</p> <p>Conclusions</p> <p>Postmenopausal women currently using HT had improved sleep quality for two out of five objective measures: shorter WASO and fewer long-wake episodes. The mechanism behind these associations is not clear. For postmenopausal women, starting HT use should be considered carefully in balance with other risks since the vascular side-effects of hormone replacement may exceed its beneficial effects on sleep.</p

    The complex genetics of gait speed:Genome-wide meta-analysis approach

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    Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging

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