A Perspective on PEF Synthesis, Properties, and End-Life

This critical review considers the extensive research and development dedicated, in the last years, to a single polymer, the poly(ethylene 2,5-furandicarboxylate), usually simply referred to as PEF. PEF importance stems from the fact that it is based on renewable resources, typically prepared from C6 sugars present in biomass feedstocks, for its resemblance to the high-performance poly(ethylene terephthalate) (PET) and in terms of barrier properties even outperforming PET. For the first time synthesis, properties, and end-life targeting-a more sustainable PEF-are critically reviewed. The emphasis is placed on how synthetic roots to PEF evolved toward the development of greener processes based on ring open polymerization, enzymatic synthesis, or the use of ionic liquids; together with a broader perspective on PEF end-life, highlighting recycling and (bio)degradation solutions

Brain transcriptomic profiling reveals common alterations across neurodegenerative and psychiatric disorders

Neurodegenerative and neuropsychiatric disorders (ND-NPs) are multifactorial, polygenic and complex behavioral phenotypes caused by brain abnormalities. Large-scale collaborative efforts have tried to identify the genetic architecture of these conditions. However, the specific and shared underlying molecular pathobiology of brain illnesses is not clear. Here, we examine transcriptome-wide characterization of eight conditions, using a total of 2,633 post-mortem brain samples from patients with Alzheimer’s disease (AD), Parkinson’s disease (PD), Progressive Supranuclear Palsy (PSP), Pathological Aging (PA), Autism Spectrum Disorder (ASD), Schizophrenia (Scz), Major Depressive Disorder (MDD), and Bipolar Disorder (BP)–in comparison with 2,078 brain samples from matched control subjects. Similar transcriptome alterations were observed between NDs and NPs with the top correlations obtained between Scz-BP, ASD-PD, AD-PD, and Scz-ASD. Region-specific comparisons also revealed shared transcriptome alterations in frontal and temporal lobes across NPs and NDs. Co-expression network analysis identified coordinated dysregulations of cell-type-specific modules across NDs and NPs. This study provides a transcriptomic framework to understand the molecular alterations of NPs and NDs through their shared- and specific gene expression in the brain

Gene finding in the chicken genome

BACKGROUND: Despite the continuous production of genome sequence for a number of organisms, reliable, comprehensive, and cost effective gene prediction remains problematic. This is particularly true for genomes for which there is not a large collection of known gene sequences, such as the recently published chicken genome. We used the chicken sequence to test comparative and homology-based gene-finding methods followed by experimental validation as an effective genome annotation method. RESULTS: We performed experimental evaluation by RT-PCR of three different computational gene finders, Ensembl, SGP2 and TWINSCAN, applied to the chicken genome. A Venn diagram was computed and each component of it was evaluated. The results showed that de novo comparative methods can identify up to about 700 chicken genes with no previous evidence of expression, and can correctly extend about 40% of homology-based predictions at the 5' end. CONCLUSIONS: De novo comparative gene prediction followed by experimental verification is effective at enhancing the annotation of the newly sequenced genomes provided by standard homology-based methods

Defining functional DNA elements in the human genome

With the completion of the human genome sequence, attention turned to identifying and annotating its functional DNA elements. As a complement to genetic and comparative genomics approaches, the Encyclopedia of DNA Elements Project was launched to contribute maps of RNA transcripts, transcriptional regulator binding sites, and chromatin states in many cell types. The resulting genome-wide data reveal sites of biochemical activity with high positional resolution and cell type specificity that facilitate studies of gene regulation and interpretation of noncoding variants associated with human disease. However, the biochemically active regions cover a much larger fraction of the genome than do evolutionarily conserved regions, raising the question of whether nonconserved but biochemically active regions are truly functional. Here, we review the strengths and limitations of biochemical, evolutionary, and genetic approaches for defining functional DNA segments, potential sources for the observed differences in estimated genomic coverage, and the biological implications of these discrepancies. We also analyze the relationship between signal intensity, genomic coverage, and evolutionary conservation. Our results reinforce the principle that each approach provides complementary information and that we need to use combinations of all three to elucidate genome function in human biology and disease

Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells

Characterizing the multifaceted contribution of genetic and epigenetic factors to disease phenotypes is a major challenge in human genetics and medicine. We carried out high-resolution genetic, epigenetic, and transcriptomic profiling in three major human immune cell types (CD14$^{+}$ monocytes, CD16$^{+}$ neutrophils, and naive CD4$^{+}$ T cells) from up to 197 individuals. We assess, quantitatively, the relative contribution of $\textit{cis}$-genetic and epigenetic factors to transcription and evaluate their impact as potential sources of confounding in epigenome-wide association studies. Further, we characterize highly coordinated genetic effects on gene expression, methylation, and histone variation through quantitative trait locus (QTL) mapping and allele-specific (AS) analyses. Finally, we demonstrate colocalization of molecular trait QTLs at 345 unique immune disease loci. This expansive, high-resolution atlas of multi-omics changes yields insights into cell-type-specific correlation between diverse genomic inputs, more generalizable correlations between these inputs, and defines molecular events that may underpin complex disease risk.This work was predominantly funded by the EU FP7 High Impact Project BLUEPRINT (HEALTH-F5-2011-282510) and the Canadian Institutes of Health Research (CIHR EP1-120608). The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no 282510 (BLUEPRINT), the European Molecular Biology Laboratory, the Max Planck society, the Spanish Ministry of Economy and Competitiveness, ‘Centro de Excelencia Severo Ochoa 2013-2017’, SEV-2012-0208 and Spanish National Bioinformatics Institute (INB-ISCIII) PT13/0001/0021 co-funded by FEDER "“Una Manera de hacer Europa”. D.G. is supported by a “la Caixa”-Severo Ochoa pre-doctoral fellowship, M.F. was supported by the BHF Cambridge Centre of Excellence [RE/13/6/30180], K.D. is funded as a HSST trainee by NHS Health Education England, S.E. is supported by a fellowship from La Caixa, V.P. is supported by a FEBS long-term fellowship and N.S.'s research is supported by the Wellcome Trust (Grant Codes WT098051 and WT091310), the EU FP7 (EPIGENESYS Grant Code 257082 and BLUEPRINT Grant Code HEALTH-F5-2011-282510) and the NIHR BRC. The Blood and Transplant Unit (BTRU) in Donor Health and Genomics is part of and funded by the National Institute for Health Research (NIHR) and is a partnership between the University of Cambridge and NHS Blood and Transplant (NHSBT) in collaboration with the University of Oxford and the Wellcome Trust Sanger Institute. The T-cell data was produced by the McGill Epigenomics Mapping Centre (EMC McGill). It is funded under the Canadian Epigenetics, Environment, and Health Research Consortium (CEEHRC) by the Canadian Institutes of Health Research and by Genome Quebec (CIHR EP1-120608), with additional support from Genome Canada and FRSQ. T.P. holds a Canada Research Chair

Features generated for computational splice-site prediction correspond to functional elements

<p>Abstract</p> <p>Background</p> <p>Accurate selection of splice sites during the splicing of precursors to messenger RNA requires both relatively well-characterized signals at the splice sites and auxiliary signals in the adjacent exons and introns. We previously described a feature generation algorithm (FGA) that is capable of achieving high classification accuracy on human 3' splice sites. In this paper, we extend the splice-site prediction to 5' splice sites and explore the generated features for biologically meaningful splicing signals.</p> <p>Results</p> <p>We present examples from the observed features that correspond to known signals, both core signals (including the branch site and pyrimidine tract) and auxiliary signals (including GGG triplets and exon splicing enhancers). We present evidence that features identified by FGA include splicing signals not found by other methods.</p> <p>Conclusion</p> <p>Our generated features capture known biological signals in the expected sequence interval flanking splice sites. The method can be easily applied to other species and to similar classification problems, such as tissue-specific regulatory elements, polyadenylation sites, promoters, etc.</p

Modelling Reveals Kinetic Advantages of Co-Transcriptional Splicing

Messenger RNA splicing is an essential and complex process for the removal of intron sequences. Whereas the composition of the splicing machinery is mostly known, the kinetics of splicing, the catalytic activity of splicing factors and the interdependency of transcription, splicing and mRNA 3′ end formation are less well understood. We propose a stochastic model of splicing kinetics that explains data obtained from high-resolution kinetic analyses of transcription, splicing and 3′ end formation during induction of an intron-containing reporter gene in budding yeast. Modelling reveals co-transcriptional splicing to be the most probable and most efficient splicing pathway for the reporter transcripts, due in part to a positive feedback mechanism for co-transcriptional second step splicing. Model comparison is used to assess the alternative representations of reactions. Modelling also indicates the functional coupling of transcription and splicing, because both the rate of initiation of transcription and the probability that step one of splicing occurs co-transcriptionally are reduced, when the second step of splicing is abolished in a mutant reporter

Symposium on the Scottish labour market

In the post-war period, up to the late 1960s, Britain enjoyed a modicum of unemployment and government policies which were geared to producing Full Employment were considered a success. It was simple - boost demand and more people would find work. But the mid 1970s the economic regency enjoyed by those advocating demand sided policies fell into disrepute as the OPEC nations raised prices dramatically and brought in a new era of both rising prices and unemployment. The laws of economics, which previously had viewed policy decisions as the choice between lower unemployment and higher inflation were now redundant. Both unemployment and inflation were moving in the same direction. The era of stagflation had begun

Finding the missing honey bee genes: lessons learned from a genome upgrade

BACKGROUND: The first generation of genome sequence assemblies and annotations have had a significant impact upon our understanding of the biology of the sequenced species, the phylogenetic relationships among species, the study of populations within and across species, and have informed the biology of humans. As only a few Metazoan genomes are approaching finished quality (human, mouse, fly and worm), there is room for improvement of most genome assemblies. The honey bee (Apis mellifera) genome, published in 2006, was noted for its bimodal GC content distribution that affected the quality of the assembly in some regions and for fewer genes in the initial gene set (OGSv1.0) compared to what would be expected based on other sequenced insect genomes. RESULTS: Here, we report an improved honey bee genome assembly (Amel_4.5) with a new gene annotation set (OGSv3.2), and show that the honey bee genome contains a number of genes similar to that of other insect genomes, contrary to what was suggested in OGSv1.0. The new genome assembly is more contiguous and complete and the new gene set includes ~5000 more protein-coding genes, 50% more than previously reported. About 1/6 of the additional genes were due to improvements to the assembly, and the remaining were inferred based on new RNAseq and protein data. CONCLUSIONS: Lessons learned from this genome upgrade have important implications for future genome sequencing projects. Furthermore, the improvements significantly enhance genomic resources for the honey bee, a key model for social behavior and essential to global ecology through pollination.Funding for the project was provided by a grant to RG from the National Human Genome Research Institute, National Institutes of Health (NHGRI, NIH) U54 HG003273. Contributions from members of the CGE lab were supported by Agriculture and Food Research Initiative Competitive grant no. 2010- 65205-20407 from the USDA National Institute of Food Agriculture. AKB was supported by a Clare Luce Booth Fellowship at Georgetown University