Predicting gene ontology from a global meta-analysis of 1-color microarray experiments

<p>Abstract</p> <p>Background</p> <p>Global meta-analysis (GMA) of microarray data to identify genes with highly similar co-expression profiles is emerging as an accurate method to predict gene function and phenotype, even in the absence of published data on the gene(s) being analyzed. With a third of human genes still uncharacterized, this approach is a promising way to direct experiments and rapidly understand the biological roles of genes. To predict function for genes of interest, GMA relies on a guilt-by-association approach to identify sets of genes with known functions that are consistently co-expressed with it across different experimental conditions, suggesting coordinated regulation for a specific biological purpose. Our goal here is to define how sample, dataset size and ranking parameters affect prediction performance.</p> <p>Results</p> <p>13,000 human 1-color microarrays were downloaded from GEO for GMA analysis. Prediction performance was benchmarked by calculating the distance within the Gene Ontology (GO) tree between predicted function and annotated function for sets of 100 randomly selected genes. We find the number of new predicted functions rises as more datasets are added, but begins to saturate at a sample size of approximately 2,000 experiments. For the gene set used to predict function, we find precision to be higher with smaller set sizes, yet with correspondingly poor recall and, as set size is increased, recall and F-measure also tend to increase but at the cost of precision.</p> <p>Conclusions</p> <p>Of the 20,813 genes expressed in 50 or more experiments, at least one predicted GO category was found for 72.5% of them. Of the 5,720 genes without GO annotation, 4,189 had at least one predicted ontology using top 40 co-expressed genes for prediction analysis. For the remaining 1,531 genes without GO predictions or annotations, ~17% (257 genes) had sufficient co-expression data yet no statistically significantly overrepresented ontologies, suggesting their regulation may be more complex.</p

Can an evolutionary perspective shed light on maternal abuse of children?

Although the theory of evolution lies at the heart of contemporary biology, its influence on the study of child psychology and psychiatry has been limited. In earlier work we have argued that evolutionary thinking has much of value for clinicians. Here, we explore the possible significance of evolutionary theory for understanding child abuse by mothers, particularly neglect, emotional abuse and physical abuse. We draw on the research of anthropologists, primatologists and evolutionary theorists to make predictions about the environmental circumstances under which one would expect such abuse to be more prevalent. We discuss how in modern, Western cultures there is less understanding of the circumstances that may influence, even predispose, a mother to limit her emotional and material commitment to an infant or child. We use four short vignettes of clinical cases and one longer case description to illustrate the insights offered to clinicians by an evolutionary approach. We see our work both as contributing to greater understanding of these matters and as facilitating more compassionate models of care and intervention for women in such circumstances

Systematic classification of non-coding RNAs by epigenomic similarity

BACKGROUND: Even though only 1.5% of the human genome is translated into proteins, recent reports indicate that most of it is transcribed into non-coding RNAs (ncRNAs), which are becoming the subject of increased scientific interest. We hypothesized that examining how different classes of ncRNAs co-localized with annotated epigenomic elements could help understand the functions, regulatory mechanisms, and relationships among ncRNA families. RESULTS: We examined 15 different ncRNA classes for statistically significant genomic co-localizations with cell type-specific chromatin segmentation states, transcription factor binding sites (TFBSs), and histone modification marks using GenomeRunner (http://www.genomerunner.org). P-values were obtained using a Chi-square test and corrected for multiple testing using the Benjamini-Hochberg procedure. We clustered and visualized the ncRNA classes by the strength of their statistical enrichments and depletions. We found piwi-interacting RNAs (piRNAs) to be depleted in regions containing activating histone modification marks, such as H3K4 mono-, di- and trimethylation, H3K27 acetylation, as well as certain TFBSs. piRNAs were further depleted in active promoters, weak transcription, and transcription elongation regions, and enriched in repressed and heterochromatic regions. Conversely, transfer RNAs (tRNAs) were depleted in heterochromatin regions and strongly enriched in regions containing activating H3K4 di- and trimethylation marks, H2az histone variant, and a variety of TFBSs. Interestingly, regions containing CTCF insulator protein binding sites were associated with tRNAs. tRNAs were also enriched in the active, weak and poised promoters and, surprisingly, in regions with repetitive/copy number variations. CONCLUSIONS: Searching for statistically significant associations between ncRNA classes and epigenomic elements permits detection of potential functional and/or regulatory relationships among ncRNA classes, and suggests cell type-specific biological roles of ncRNAs

The Life Science Exchange: a case study of a sectoral and sub-sectoral knowledge exchange programme

Background: Local and national governments have implemented sector-specific policies to support economic development through innovation, entrepreneurship and knowledge exchange. Supported by the Welsh Government through the European Regional Development Fund, The Life Science Exchange® project was created with the aim to increase interaction between stakeholders, to develop more effective knowledge exchange mechanisms, and to stimulate the formation and maintenance of long-term collaborative relationships within the Welsh life sciences ecosystem. The Life Science Exchange allowed participants to interact with other stakeholder communities (clinical, academic, business, governmental), exchange perspectives and discover new opportunities.Methods: Six sub-sector focus groups comprising over 200 senior stakeholders from academia, industry, the Welsh Government and National Health Service were established. Over 18 months, each focus group provided input to inform healthcare innovation policy and knowledge mapping exercises of their respective sub-sectors. Collaborative projects identified during the focus groups and stakeholder engagement were further developed through sandpit events and bespoke support.Results: Each sub-sector focus group produced a report outlining the significant strengths and opportunities in their respective areas of focus, made recommendations to overcome any ‘system failures’, and identified the stakeholder groups which needed to take action. A second outcome was a stakeholder-driven knowledge mapping exercise for each area of focus. Finally, the sandpit events and bespoke support resulted in participants generating more than £1.66 million in grant funding and inward investment. This article outlines four separate outcomes from the Life Science Exchange programme.Conclusions: The Life Science Exchange process has resulted in a multitude of collaborations, projects, inward investment opportunities and special interest group formations, in addition to securing over ten times its own costs in funding for Wales. The Life Science Exchange model is a simple and straightforward mechanism for a regional or national government to adapt and implement in order to improve innovation, skills, networks and knowledge exchange

ROTSE All Sky Surveys for Variable Stars I: Test Fields

The ROTSE-I experiment has generated CCD photometry for the entire Northern sky in two epochs nightly since March 1998. These sky patrol data are a powerful resource for studies of astrophysical transients. As a demonstration project, we present first results of a search for periodic variable stars derived from ROTSE-I observations. Variable identification, period determination, and type classification are conducted via automatic algorithms. In a set of nine ROTSE-I sky patrol fields covering about 2000 square degrees we identify 1781 periodic variable stars with mean magnitudes between m_v=10.0 and m_v=15.5. About 90% of these objects are newly identified as variable. Examples of many familiar types are presented. All classifications for this study have been manually confirmed. The selection criteria for this analysis have been conservatively defined, and are known to be biased against some variable classes. This preliminary study includes only 5.6% of the total ROTSE-I sky coverage, suggesting that the full ROTSE-I variable catalog will include more than 32,000 periodic variable stars.Comment: Accepted for publication in AJ 4/00. LaTeX manuscript. (28 pages, 11 postscript figures and 1 gif

The Afterglow, Energetics and Host Galaxy of the Short-Hard Gamma-Ray Burst 051221a

We present detailed optical, X-ray and radio observations of the bright afterglow of the short gamma-ray burst 051221a obtained with Gemini, Swift/XRT, and the Very Large Array, as well as optical spectra from which we measure the redshift of the burst, z=0.5464. At this redshift the isotropic-equivalent prompt energy release was about 1.5 x 10^51 erg, and using the standard afterglow synchrotron model we find that the blastwave kinetic energy is similar, E_K,iso ~ 8.4 x 10^51 erg. An observed jet break at t ~ 5 days indicates that the opening angle is ~ 7 degrees and the total beaming-corrected energy is therefore ~ 2.5 x 10^49 erg, comparable to the values inferred for previous short GRBs. We further show that the burst experienced an episode of energy injection by a factor of 3.4 between t=1.4 and 3.4 hours, which was accompanied by reverse shock emission in the radio band. This result provides continued evidence that the central engines of short GRBs may be active significantly longer than the duration of the burst and/or produce a wide range of Lorentz factors. Finally, we show that the host galaxy of GRB051221a is actively forming stars at a rate of about 1.6 M_solar/yr, but at the same time exhibits evidence for an appreciable population of old stars (~ 1 Gyr) and near solar metallicity. The lack of bright supernova emission and the low circumburst density (n ~ 10^-3 cm^-3) continue to support the idea that short bursts are not related to the death of massive stars and are instead consistent with a compact object merger. Given that the total energy release is a factor of ~ 10 larger than the predicted yield for a neutrino annihilation mechanism, this suggests that magnetohydrodynamic processes may be required to power the burst.Comment: Final version (to appear in ApJ on 20 September 2006

The Dark Side of ROTSE-III Prompt GRB Observations

We present several cases of optical observations during gamma-ray bursts (GRBs) which resulted in prompt limits but no detection of optical emission. These limits constrain the prompt optical flux densities and the optical brightness relative to the gamma-ray emission. The derived constraints fall within the range of properties observed in GRBs with prompt optical detections, though at the faint end of optical/gamma flux ratios. The presently accessible prompt optical limits do not require a different set of intrinsic or environmental GRB properties, relative to the events with prompt optical detections.Comment: ApJ accepted. 20 pages in draft manuscript form, which includes 6 pages of tables and 2 figure

Detrimental effects of duplicate reads and low complexity regions on RNA- and ChIP-seq data

Background Adapter trimming and removal of duplicate reads are common practices in next-generation sequencing pipelines. Sequencing reads ambiguously mapped to repetitive and low complexity regions can also be problematic for accurate assessment of the biological signal, yet their impact on sequencing data has not received much attention. We investigate how trimming the adapters, removing duplicates, and filtering out reads overlapping low complexity regions influence the significance of biological signal in RNA- and ChIP-seq experiments. Methods We assessed the effect of data processing steps on the alignment statistics and the functional enrichment analysis results of RNA- and ChIP-seq data. We compared differentially processed RNA-seq data with matching microarray data on the same patient samples to determine whether changes in pre-processing improved correlation between the two. We have developed a simple tool to remove low complexity regions, RepeatSoaker, available at https://github.com/mdozmorov/RepeatSoaker, and tested its effect on the alignment statistics and the results of the enrichment analyses. Results Both adapter trimming and duplicate removal moderately improved the strength of biological signals in RNA-seq and ChIP-seq data. Aggressive filtering of reads overlapping with low complexity regions, as defined by RepeatMasker, further improved the strength of biological signals, and the correlation between RNA-seq and microarray gene expression data. Conclusions Adapter trimming and duplicates removal, coupled with filtering out reads overlapping low complexity regions, is shown to increase the quality and reliability of detecting biological signals in RNA-seq and ChIP-seq data

AMSA Conference Indigenous Workshop Summary

This report summarises a two-day Indigenous Workshop at the 2022 Australian Marine Sciences Association Conference. The workshop was the seventh to be supported by the National Environmental Science Program and the most significant to date in terms of Indigenous leadership and attendance. Indigenous participants from 45 language groups joined others from government, research and non-profit agencies. Indigenous organisations expressed a clear desire to work with government and research agencies to enable effective co-development of research, and to establish a nationally coordinated approach to Indigenous-led research and monitoring. The two-day Indigenous workshop brought together Indigenous leaders and community members from across the nation. This was a rare occasion for Indigenous Australians to come together and provide input into two important focal areas. 1. Collaborate and strategise on the research priorities, opportunities and constraints for Indigenous participation and leadership in environmental research in Australia’s marine and coastal regions. 2. Discuss the need for a National Indigenous Environmental Research Network (NIERN)