Thermal sensitivity of cell metabolism of different Antarctic fish species mirrors organism temperature tolerance

Despite cold adaptation, Antarctic fish show lower growth than expected from the van’t Hoff’s Q10 rule. Protein synthesis is one of the main energy-consuming processes, which is downregulated under energy deficiency. Considering the effect of temperature on growth performance, we tested if temperature-dependent cellular energy allocation to protein synthesis correlates with temperature-dependent whole-animal growth and thus thermal tolerance. Cell respiration and energy expenditure for protein synthesis were determined in hepatocytes of the circumpolar-distributed Antarctic eelpout Pachycara brachycephalum after warm acclimation (0 °C vs 5 °C) and, of two notothenioids the sub-Antarctic Lepidonotothen squamifrons and the high-Antarctic icefish Chionodraco hamatus. We used intermittent-flow respirometry to analyse cellular response to acute warming from 5 to 10 °C (P. brachycephalum) and from 1 to 5 °C (L. squamifrons, C. hamatus). Warming-induced rise in respiration was similar between 0- and 5 °C-acclimated P. brachycephalum and between L. squamifrons and C. hamatus. Irrespective of acclimation, warming decreased energy expenditure for protein synthesis in P. brachycephalum, which corresponds to reduced whole-animal growth at temperatures > 5 °C. Warming doubled energy expenditure for protein synthesis in L. squamifrons but had no effect on C. hamatus indicating that L. squamifrons might benefit from warmer waters. The species-specific temperature effect on energy expenditure for protein synthesis is discussed to mirror thermal sensitivity of whole-animal growth performance, thereby paralleling the degree of cold adaptation. Clearly more data are necessary including measurements at narrower temperature steps particularly for C. hamatus and an increased species’ number per ecotype to reinforce presented link between cellular and whole-animal thermal sensitivity

Genome-wide analyses implicate 33 loci in heritable dog osteosarcoma, including regulatory variants near CDKN2A/B

Background: Canine osteosarcoma is clinically nearly identical to the human disease, but is common and highly heritable, making genetic dissection feasible. Results: Through genome-wide association analyses in three breeds (greyhounds, Rottweilers, and Irish wolfhounds), we identify 33 inherited risk loci explaining 55% to 85% of phenotype variance in each breed. The greyhound locus exhibiting the strongest association, located 150 kilobases upstream of the genes CDKN2A/B, is also the most rearranged locus in canine osteosarcoma tumors. The top germline candidate variant is found at a >90% frequency in Rottweilers and Irish wolfhounds, and alters an evolutionarily constrained element that we show has strong enhancer activity in human osteosarcoma cells. In all three breeds, osteosarcoma-associated loci and regions of reduced heterozygosity are enriched for genes in pathways connected to bone differentiation and growth. Several pathways, including one of genes regulated by miR124, are also enriched for somatic copy-number changes in tumors. Conclusions: Mapping a complex cancer in multiple dog breeds reveals a polygenic spectrum of germline risk factors pointing to specific pathways as drivers of disease

Integrated multi-omics reveals anaplerotic rewiring in methylmalonyl-CoA mutase deficiency

Multi-layered omics approaches can help define relationships between genetic factors, biochemical processes and phenotypes thus extending research of inherited diseases beyond identifying their monogenic cause 1. We implemented a multi-layered omics approach for the inherited metabolic disorder methylmalonic aciduria (MMA). We performed whole genome sequencing, transcriptomic sequencing, and mass spectrometry-based proteotyping from matched primary fibroblast samples of 230 individuals (210 affected, 20 controls) and related the molecular data to 105 phenotypic features. Integrative analysis identified a molecular diagnosis for 84% (177/210) of affected individuals, the majority (148) of whom had pathogenic variants in methylmalonyl-CoA mutase (MMUT). Untargeted analysis of all three omics layers revealed dysregulation of the TCA cycle and surrounding metabolic pathways, a finding that was further corroborated by multi-organ metabolomics of a hemizygous Mmut mouse model. Integration of phenotypic disease severity indicated downregulation of oxoglutarate dehydrogenase and upregulation of glutamate dehydrogenase, two proteins involved in glutamine anaplerosis of the TCA cycle. The relevance of disturbances in this pathway was supported by metabolomics and isotope tracing studies which showed decreased glutamine-derived anaplerosis in MMA. We further identified MMUT to physically interact with both, oxoglutarate dehydrogenase complex components and glutamate dehydrogenase providing evidence for a multi-protein metabolon that orchestrates TCA cycle anaplerosis. This study emphasizes the utility of a multi-modal omics approach to investigate metabolic diseases and highlights glutamine anaplerosis as a potential therapeutic intervention point in MMA. Take home message Combination of integrative multi-omics technologies with clinical and biochemical features leads to an increased diagnostic rate compared to genome sequencing alone and identifies anaplerotic rewiring as a targetable feature of the rare inborn error of metabolism methylmalonic aciduria

Quark-gluon vertex in general kinematics

The original publication can be found at www.springerlink.com Submitted to Cornell University’s online archive www.arXiv.org in 2007 by Jon-Ivar Skullerud. Post-print sourced from www.arxiv.org.We compute the quark–gluon vertex in quenched lattice QCD in the Landau gauge, using an off-shell mean-field O(a)-improved fermion action. The Dirac-vector part of the vertex is computed for arbitrary kinematics. We find a substantial infrared enhancement of the interaction strength regardless of the kinematics.Ayse Kizilersu, Derek B. Leinweber, Jon-Ivar Skullerud and Anthony G. William

Evidence for Transcript Networks Composed of Chimeric RNAs in Human Cells

The classic organization of a gene structure has followed the Jacob and Monod bacterial gene model proposed more than 50 years ago. Since then, empirical determinations of the complexity of the transcriptomes found in yeast to human has blurred the definition and physical boundaries of genes. Using multiple analysis approaches we have characterized individual gene boundaries mapping on human chromosomes 21 and 22. Analyses of the locations of the 5′ and 3′ transcriptional termini of 492 protein coding genes revealed that for 85% of these genes the boundaries extend beyond the current annotated termini, most often connecting with exons of transcripts from other well annotated genes. The biological and evolutionary importance of these chimeric transcripts is underscored by (1) the non-random interconnections of genes involved, (2) the greater phylogenetic depth of the genes involved in many chimeric interactions, (3) the coordination of the expression of connected genes and (4) the close in vivo and three dimensional proximity of the genomic regions being transcribed and contributing to parts of the chimeric RNAs. The non-random nature of the connection of the genes involved suggest that chimeric transcripts should not be studied in isolation, but together, as an RNA network

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas

GENCODE reference annotation for the human and mouse genomes

The accurate identification and description of the genes in the human and mouse genomes is a fundamental requirement for high quality analysis of data informing both genome biology and clinical genomics. Over the last 15 years, the GENCODE consortium has been producing reference quality gene annotations to provide this foundational resource. The GENCODE consortium includes both experimental and computational biology groups who work together to improve and extend the GENCODE gene annotation. Specifically, we generate primary data, create bioinformatics tools and provide analysis to support the work of expert manual gene annotators and automated gene annotation pipelines. In addition, manual and computational annotation workflows use any and all publicly available data and analysis, along with the research literature to identify and characterise gene loci to the highest standard. GENCODE gene annotations are accessible via the Ensembl and UCSC Genome Browsers, the Ensembl FTP site, Ensembl Biomart, Ensembl Perl and REST APIs as well as https://www.gencodegenes.org.National Human Genome Research Institute of the National Institutes of Healt

Comparative analysis of the transcriptome across distant species

The transcriptome is the readout of the genome. Identifying common features in it across distant species can reveal fundamental principles. To this end, the ENCODE and modENCODE consortia have generated large amounts of matched RNA-sequencing data for human, worm and fly. Uniform processing and comprehensive annotation of these data allow comparison across metazoan phyla, extending beyond earlier within-phylum transcriptome comparisons and revealing ancient, conserved features. Specifically, we discover co-expression modules shared across animals, many of which are enriched in developmental genes. Moreover, we use expression patterns to align the stages in worm and fly development and find a novel pairing between worm embryo and fly pupae, in addition to the embryo-to-embryo and larvae-to-larvae pairings. Furthermore, we find that the extent of non-canonical, non-coding transcription is similar in each organism, per base pair. Finally, we find in all three organisms that the gene-expression levels, both coding and non-coding, can be quantitatively predicted from chromatin features at the promoter using a 'universal model' based on a single set of organism-independent parameters

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease