The Marmot Review: Updated data and information 2 years on

To mark the two year anniversary since The Marmot Review ('Fair Society, Healthy Lives') was published, on the 15th of February the UCL Institute of Health Equity published new data on key health inequalities indicators at local authority level in England.Main Findings:Life Expectancy – this has historically been one of the main indicators of health inequalities.The Marmot Indicators from this year’s charts show the average life expectancy for eachlocal authority and the level of inequality within each authority area (7):-While overall life expectancy at birth in England increased by 0.3 years for both menand women between 2007-9 and 2008-10, inequalities in life expectancy betweenneighbourhoods increased by 0.1 years for men and showed no change for women-Among the 150 upper tier local authorities in England, life expectancy improved inthe majority of cases (133 areas saw improvements for men and 125 sawimprovements for women). However inequalities also increased in the majority ofareas (104 for men and 92 for women).-The largest increase in inequality in life expectancy was in West Berkshire for men(2.0 years) and inMiddlesbrough for women (2 years). The largest decreases ininequality were in Kensington and Chelsea for both men and women (1.9 and 1.1years respectively. To find out more, please read: - The press release, including key figures and main findings. - A blog by Michael Marmot about the data and it's implications. - Press coverage of the data in national and local newspapers and websites. - A powerpoint presentation on the key findings.

Affymetrix Whole-Transcript Human Gene 1.0 ST array is highly concordant with standard 3' expression arrays.

The recently released Affymetrix Human Gene 1.0 ST array has two major differences compared with standard 3' based arrays: (i) it interrogates the entire mRNA transcript, and (ii) it uses DNA targets. To assess the impact of these differences on array performance, we performed a series of comparative hybridizations between the Human Gene 1.0 ST and the Affymetrix HG-U133 Plus 2.0 and the Illumina HumanRef-8 BeadChip arrays. Additionally, both RNA and DNA targets were hybridized on HG-U133 Plus 2.0 arrays. The results show that the overall reproducibility of the Gene 1.0 ST array is best. When looking only at the high intensity probes, the reproducibility of the Gene 1.0 ST array and the Illumina BeadChip array is equally good. Concordance of array results was assessed using different inter-platform mappings. Agreements are best between the two labeling protocols using HG-U133 Plus 2.0 array. The Gene 1.0 ST array is most concordant with the HG-U133 array hybridized with cDNA targets. This may reflect the impact of the target type. Overall, the high degree of correspondence provides strong evidence for the reliability of the Gene 1.0 ST array.

SelenoDB 1.0 : a database of selenoprotein genes, proteins and SECIS elements

Selenoproteins are a diverse group of proteinsusually misidentified and misannotated in sequencedatabases. The presence of an in-frame UGA (stop)codon in the coding sequence of selenoproteingenes precludes their identification and correctannotation. The in-frame UGA codons are recodedto cotranslationally incorporate selenocysteine,a rare selenium-containing amino acid. The developmentof ad hoc experimental and, more recently,computational approaches have allowed the efficientidentification and characterization of theselenoproteomes of a growing number of species.Today, dozens of selenoprotein families have beendescribed and more are being discovered in recentlysequenced species, but the correct genomic annotationis not available for the majority of thesegenes. SelenoDB is a long-term project that aims toprovide, through the collaborative effort of experimentaland computational researchers, automaticand manually curated annotations of selenoproteingenes, proteins and SECIS elements. Version 1.0 ofthe database includes an initial set of eukaryoticgenomic annotations, with special emphasis on thehuman selenoproteome, for immediate inspectionby selenium researchers or incorporation into moregeneral databases. SelenoDB is freely available athttp://www.selenodb.org.

A short motif in Drosophila SECIS Binding Protein 2 provides differential binding affinity to SECIS RNA hairpins

Selenoproteins contain the amino acid selenocysteine which is encoded by a UGA Sec codon. Recoding UGA Sec requires a complex mechanism, comprising the cis-acting SECIS RNA hairpin in the 3′UTR of selenoprotein mRNAs, and trans-acting factors. Among these, the SECIS Binding Protein 2 (SBP2) is central to the mechanism. SBP2 has been so far functionally characterized only in rats and humans. In this work, we report the characterization of the Drosophila melanogaster SBP2 (dSBP2). Despite its shorter length, it retained the same selenoprotein synthesis-promoting capabilities as the mammalian counterpart. However, a major difference resides in the SECIS recognition pattern: while human SBP2 (hSBP2) binds the distinct form 1 and 2 SECIS RNAs with similar affinities, dSBP2 exhibits high affinity toward form 2 only. In addition, we report the identification of a K (lysine)-rich domain in all SBP2s, essential for SECIS and 60S ribosomal subunit binding, differing from the well-characterized L7Ae RNA-binding domain. Swapping only five amino acids between dSBP2 and hSBP2 in the K-rich domain conferred reversed SECIS-binding properties to the proteins, thus unveiling an important sequence for form 1 binding.

FGF signaling controls caudal hindbrain specification through Ras-ERK1/2 pathway

Background: During early steps of embryonic development the hindbrain undergoes a regionalization process along the anterior-posterior (AP) axis that leads to a metameric organization in a series of rhombomeres (r). Refinement of the AP identities within the hindbrain requires the establishment of local signaling centers, which emit signals that pattern territories in their vicinity. Previous results demonstrated that the transcription factor vHnf1 confers caudal identity to the hindbrain inducing Krox20 in r5 and MafB/Kreisler in r5 and r6, through FGF signaling [1].Results: We show that in the chick hindbrain, Fgf3 is transcriptionally activated as early as 30 min after mvHnf1 electroporation, suggesting that it is a direct target of this transcription factor. We also analyzed the expression profiles of FGF activity readouts, such as MKP3 and Pea3, and showed that both are expressed within the hindbrain at early stages of embryonic development. In addition, MKP3 is induced upon overexpression of mFgf3 or mvHnf1 in the hindbrain, confirming vHnf1 is upstream FGF signaling. Finally, we addressed the question of which of the FGF-responding intracellular pathways were active and involved in the regulation of Krox20 and MafB in the hindbrain. While Ras-ERK1/2 activity is necessary for MKP3, Krox20 and MafB induction, PI3K-Akt is not involved in that process.Conclusion: Based on these observations we propose that vHnf1 acts directly through FGF3, and promotes caudal hindbrain identity by activating MafB and Krox20 via the Ras-ERK1/2 intracellular pathway.

OSIRISv1.2: a named entity recognition system for sequence variants of genes in biomedical literature

Background: Single Nucleotide Polymorphisms, among other type of sequence variants, constitute key elements in genetic epidemiology and pharmacogenomics. While sequence data about genetic variation is found at databases such as dbSNP, clues about the functional and phenotypic consequences of the variations are generally found in biomedical literature. The identification of the relevant documents and the extraction of the information from them are hampered by the large size of literature databases and the lack of widely accepted standard notation for biomedical entities. Thus, automatic systems for the identification of citations of allelic variants of genes in biomedical texts are required. Results: Our group has previously reported the development of OSIRIS, a system aimed at the retrieval of literature about allelic variants of genes http://ibi.imim.es/osirisform.html. Here we describe the development of a new version of OSIRIS (OSIRISv1.2, http://ibi.imim.es/OSIRISv1.2.html webcite) which incorporates a new entity recognition module and is built on top of a local mirror of the MEDLINE collection and HgenetInfoDB: a database that collects data on human gene sequence variations. The new entity recognition module is based on a pattern-based search algorithm for the identification of variation terms in the texts and their mapping to dbSNP identifiers. The performance of OSIRISv1.2 was evaluated on a manually annotated corpus, resulting in 99% precision, 82% recall, and an F-score of 0.89. As an example, the application of the system for collecting literature citations for the allelic variants of genes related to the diseases intracranial aneurysm and breast cancer is presented. Conclusion: OSIRISv1.2 can be used to link literature references to dbSNP database entries with high accuracy, and therefore is suitable for collecting current knowledge on gene sequence variations and supporting the functional annotation of variation databases. The application of OSIRISv1.2 in combination with controlled vocabularies like MeSH provides a way to identify associations of biomedical interest, such as those that relate SNPs with diseases.