SnoPatrol: how many snoRNA genes are there?

Small nucleolar RNAs (snoRNAs) are among the most evolutionarily ancient classes of small RNA. Two experimental screens published in BMC Genomics expand the eukaryotic snoRNA catalog, but many more snoRNAs remain to be found

Transporting Evidence-Based Parenting Programs for Child Problem Behavior (Age 3–10) Between Countries::Systematic Review and Meta-Analysis

There has been rapid global dissemination of parenting interventions, yet little is known about their effectiveness when transported to countries different from where they originated, or about factors influencing success. This is the first systematic attempt to address this issue, focusing on interventions for reducing child behavior problems. Stage 1 identified evidence-based parenting interventions showing robust effects in systematic reviews; Stage 2 identified trials of these interventions in a new country. Systematic review/meta-analysis of transported programs was followed by subgroup analyses by trial- and country-level cultural, resource, and policy factors. We found 17 transported trials of 4 interventions, originating in United States or Australia, tested in 10 countries in 5 regions, (n = 1,558 children). Effects on child behavior were substantial (SMD −.71) in the (14) randomized trials, but nonsignificant in the (3) nonrandomized trials. Subgroup analyses of randomized trials found no association between effect size and participant or intervention factors (e.g., program brand, staffing). Interventions transported to “western” countries showed comparable effects to trials in origin countries; however, effects were stronger when interventions were transported to culturally more distant regions. Effects were higher in countries with survival-focused family/childrearing values than those ranked more individualistic. There were no differences in effects by country-level policy or resource factors. Contrary to common belief, parenting interventions appear to be at least as effective when transported to countries that are more different culturally, and in service provision, than those in which they were developed. Extensive adaptation did not appear necessary for successful transportation

Comparative Analysis of RNA Families Reveals Distinct Repertoires for Each Domain of Life

The RNA world hypothesis, that RNA genomes and catalysts preceded DNA genomes and genetically-encoded protein catalysts, has been central to models for the early evolution of life on Earth. A key part of such models is continuity between the earliest stages in the evolution of life and the RNA repertoires of extant lineages. Some assessments seem consistent with a diverse RNA world, yet direct continuity between modern RNAs and an RNA world has not been demonstrated for the majority of RNA families, and, anecdotally, many RNA functions appear restricted in their distribution. Despite much discussion of the possible antiquity of RNA families, no systematic analyses of RNA family distribution have been performed. To chart the broad evolutionary history of known RNA families, we performed comparative genomic analysis of over 3 million RNA annotations spanning 1446 families from the Rfam 10 database. We report that 99% of known RNA families are restricted to a single domain of life, revealing discrete repertoires for each domain. For the 1% of RNA families/clans present in more than one domain, over half show evidence of horizontal gene transfer, and the rest show a vertical trace, indicating the presence of a complex protein synthesis machinery in the Last Universal Common Ancestor (LUCA) and consistent with the evolutionary history of the most ancient protein-coding genes. However, with limited interdomain transfer and few RNA families exhibiting demonstrable antiquity as predicted under RNA world continuity, our results indicate that the majority of modern cellular RNA repertoires have primarily evolved in a domain-specific manner.Comment: 47 pages, 4 main figures, 3 supplementary figures, 4 supplementary tables. Submitted to PLOS Computational Biolog

Essential guidelines for computational method benchmarking

In computational biology and other sciences, researchers are frequently faced with a choice between several computational methods for performing data analyses. Benchmarking studies aim to rigorously compare the performance of different methods using well-characterized benchmark datasets, to determine the strengths of each method or to provide recommendations regarding suitable choices of methods for an analysis. However, benchmarking studies must be carefully designed and implemented to provide accurate, unbiased, and informative results. Here, we summarize key practical guidelines and recommendations for performing high-quality benchmarking analyses, based on our experiences in computational biology.Comment: Minor update

Use of tiling array data and RNA secondary structure predictions to identify noncoding RNA genes

<p>Abstract</p> <p>Background</p> <p>Within the last decade a large number of noncoding RNA genes have been identified, but this may only be the tip of the iceberg. Using comparative genomics a large number of sequences that have signals concordant with conserved RNA secondary structures have been discovered in the human genome. Moreover, genome wide transcription profiling with tiling arrays indicate that the majority of the genome is transcribed.</p> <p>Results</p> <p>We have combined tiling array data with genome wide structural RNA predictions to search for novel noncoding and structural RNA genes that are expressed in the human neuroblastoma cell line SK-N-AS. Using this strategy, we identify thousands of human candidate RNA genes. To further verify the expression of these genes, we focused on candidate genes that had a stable hairpin structures or a high level of covariance. Using northern blotting, we verify the expression of 2 out of 3 of the hairpin structures and 3 out of 9 high covariance structures in SK-N-AS cells.</p> <p>Conclusion</p> <p>Our results demonstrate that many human noncoding, structured and conserved RNA genes remain to be discovered and that tissue specific tiling array data can be used in combination with computational predictions of sequences encoding structural RNAs to improve the search for such genes.</p

Essential guidelines for computational method benchmarking

In computational biology and other sciences, researchers are frequently faced with a choice between several computational methods for performing data analyses. Benchmarking studies aim to rigorously compare the performance of different methods using well-characterized benchmark datasets, to determine the strengths of each method or to provide recommendations regarding suitable choices of methods for an analysis. However, benchmarking studies must be carefully designed and implemented to provide accurate, unbiased, and informative results. Here, we summarize key practical guidelines and recommendations for performing high-quality benchmarking analyses, based on our experiences in computational biology

Identification of miRNA targets with stable isotope labeling by amino acids in cell culture

miRNAs are small noncoding RNAs that regulate gene expression. We have used stable isotope labeling by amino acids in cell culture (SILAC) to investigate the effect of miRNA-1 on the HeLa cell proteome. Expression of 12 out of 504 investigated proteins was repressed by miRNA-1 transfection. This repressed set of genes significantly overlaps with miRNA-1 regulated genes that have been identified with DNA array technology and are predicted by computational methods. Moreover, we find that the 3′-untranslated region for the repressed set are enriched in miRNA-1 complementary sites. Our findings demonstrate that SILAC can be used for miRNA target identification and that one highly expressed miRNA can regulate the levels of many different proteins

A Deep Multicolor Survey. VI. Near-Infrared Observations, Selection Effects, and Number Counts

I present near-infrared J (1.25um), H (1.65um), and K (2.2um) imaging observations of 185 square arcminutes in 21 high galactic latitude fields. These observations reach limiting magnitudes of J ~ 21 mag, H ~ 20 mag and K ~ 18.5 mag. The detection efficiency, photometric accuracy and selection biases as a function of integrated object brightness, size, and profile shape are quantified in detail. I evaluate several popular methods for measuring the integrated light of faint galaxies and show that only aperture magnitudes provide an unbiased measure of the integrated light that is independent of apparent magnitude. These J, H, and K counts and near-infrared colors are in best agreement with passive galaxy formation models with at most a small amount of merging (for Omega_M = 0.3, Omega_Lambda = 0.7).Comment: AJ Accepted (Feb 2001). 28 pages, 7 embedded ps figures, AASTEX5. Minor changes to submitted version. Also available at http://www.astronomy.ohio-state.edu/~martini/pubs

Energy and Climate Change: Key Lessons for Implementing the Behavioral Wedge

The individual and household sector accounts for roughly 40 percent of United States energy use and carbon dioxide emissions, yet the laws and policies directed at reductions from this sector often reflect a remarkably simplistic model of behavior. This Essay addresses one of the obstacles to achieving a “behavioral wedge” of individual and household emissions reductions: the lack of an accessible, brief summary for policymakers of the key findings of behavioral and social science studies on household energy behavior. The Essay does not provide a comprehensive overview of the field, but it discusses many of the leading studies that demonstrate the extent and limits of rational action. These studies can inform lawyers and policymakers who are developing measures to reduce energy use and carbon emissions and can serve as an entry point for more detailed studies of the literature. An effective response to the climate change problem will require substantial reductions in energy demand in addition to new developments in low-carbon energy supplies. The individual and household sector presents a major opportunity: the sector accounts for roughly 40% of U.S. carbon emissions and a comparable percentage of total U.S. energy production, and it is one of the most promising areas for reducing emissions. A recent analysis estimates that behavioral measures directed at this sector could reasonably be expected to reduce total US emissions by over 7% by 2020, an amount larger than the combined emissions from several of the largest-emitting industrial sectors and larger than the total emissions of France. In many cases, these emissions reductions can be achieved at less cost than the leading alternatives. Despite this opportunity, recent regulatory and policy efforts are only beginning to direct substantial attention to the individual and household sector. Findings from the social sciences provide valuable insights into how to capitalize on this opportunity, yet policymakers often have little time to develop new polices and are confronted with a barrage of often-conflicting approaches and theories. This Essay addresses the policy-making challenge by distilling the findings from a broad range of fields into several key principles for those developing energy and climate laws and policies. The principles we outline here are a starting point for policymakers working in this area. We attempt to provide insight into which principles are most relevant to law and policy, but instructions as to how to incorporate these principles are beyond the scope of this essay. The principles include only a subset of the insights from the behavioral and social science literature. In many cases, adherence to multiple principles will be necessary to develop the most effective policy design. Policymakers should consult the body of work referenced here, as well as experts in the social sciences to further their understanding of these and other principles. More extensive reviews of this literature and its relevance to energy and climate policy are also available

Activation of alpha4* nAChRs is necessary and sufficient for varenicline-induced reduction of alcohol consumption

Recently, the smoking cessation therapeutic varenicline, a nicotinic acetylcholine receptor (nAChR) partial agonist, has been shown to reduce alcohol consumption. However, the mechanism and nAChR subtype(s) involved are unknown. Here we demonstrate that varenicline and alcohol exposure, either alone or in combination, selectively activates dopaminergic (DAergic) neurons within the posterior, but not the anterior, ventral tegmental area (VTA). To gain insight into which nAChR subtypes may be involved in the response to alcohol, we analyzed nAChR subunit gene expression in posterior VTA DAergic neurons. Ethanol-activated DAergic neurons expressed higher levels of alpha4, alpha6, and beta3 subunit genes compared with nonactivated neurons. To examine the role of nicotinic receptors containing the alpha4 subunit (alpha4* nAChRs) in varenicline-induced reduction of alcohol consumption, we examined the effect of the drug in two complementary mouse models, a knock-out line that does not express the alpha4 subunit (alpha4 KO) and another line that expresses alpha4* nAChRs hypersensitive to agonist (Leu9\u27Ala). While varenicline (0.1-0.3 mg/kg, i.p.) reduced 2% and 20% alcohol consumption in wild-type (WT) mice, the drug did not significantly reduce consumption in alpha4 KO animals. Conversely, low doses of varenicline (0.0125-0.05 mg/kg, i.p.) that had little effect in WT mice dramatically reduced ethanol intake in Leu9\u27Ala mice. Infusion of varenicline into the posterior, but not the anterior VTA was sufficient to reduce alcohol consumption. Together, our data indicate that activation of alpha4* nAChRs is necessary and sufficient for varenicline reduction of alcohol consumption