A star formation study of the ATLAS3D early-type galaxies with the AKARI all-sky survey

The star formation properties of early-type galaxies (ETGs) are currently the subject of considerable interest, particularly whether they differ from those of gas-rich spirals. We perform a systematic study of star formation in a large sample of local ETGs using polycyclic aromatic hydrocarbon (PAH) and dust emission, focusing on the galaxies' star formation rates (SFRs) and star formation efficiencies (SFEs). Our sample is composed of the 260 ETGs from the ATLAS3D survey, from which we use the cold gas measurements (HI and CO). The SFRs are estimated from stellar, PAH and dust fits to spectral energy distributions created from new AKARI measurements and literature data from WISE and 2MASS. The mid-infrared luminosities of non-CO-detected galaxies are well correlated with their stellar luminosities, showing that they trace (circum)stellar dust emission. CO-detected galaxies show an excess above these correlations, uncorrelated with their stellar luminosities, indicating that they likely contain PAHs and dust of interstellar origin. PAH and dust luminosities of CO-detected galaxies show tight correlations with their molecular gas masses, and the derived current SFRs are typically 0.01-1 Msun/yr. These SFRs systematically decrease with stellar age at fixed stellar mass, while they correlate nearly linearly with stellar mass at fixed age. The majority of local ETGs follow the same star-formation law as local star-forming galaxies, and their current SFEs do not depend on either stellar mass or age. Our results clearly indicate that molecular gas is fueling current star formation in local ETGs, that appear to acquire this gas via mechanisms regulated primarily by stellar mass. The current SFEs of local ETGs are similar to those of local star-forming galaxies, indicating that their low SFRs are likely due to smaller cold gas fractions rather than a suppression of star formation.Comment: 30 pages, 12 figures, 4 tables, accepted for publication in A&

Safety of batteries in insulin pumps

Aims/Introduction: We investigated the safety of the batteries and power units used in insulin pumps in Japan. Materials and Methods: A self‐administered questionnaire was sent to the 201 members of the Association for Innovative Diabetes Treatment in Japan. Results: A total of 56 members responded, and among the 1,499 active devices, 66 had episodes of trouble related to the batteries and power units. The ratio of reported troubles to the number of insulin pumps was significantly higher in insulin pumps with a continuous glucose monitoring sensor compared with insulin pumps without a continuous glucose monitoring sensor (odds ratio 2.82, P < 0.05). The cause and the consequences varied. The brands of the batteries varied; alkaline batteries purchased at drug stores and other shops accounted for 19.7%. Termination of battery life within 72 h of use was reported most frequently (50.0%), suspension of the insulin pump (21.2%) and leakage of the battery fluid (4.5%) followed. A total of 53.2% of the reported insulin pumps needed to be replaced, and 37.1% of them recovered after replacement of the battery. Conclusions: As trouble related to the batteries and power units of insulin pumps was frequent, practical guidance should be provided to respective patients regarding the use of reliable batteries, and to be well prepared for unexpected insulin pump failure

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism

Gene Organization in Rice Revealed by Full-Length cDNA Mapping and Gene Expression Analysis through Microarray

Rice (Oryza sativa L.) is a model organism for the functional genomics of monocotyledonous plants since the genome size is considerably smaller than those of other monocotyledonous plants. Although highly accurate genome sequences of indica and japonica rice are available, additional resources such as full-length complementary DNA (FL-cDNA) sequences are also indispensable for comprehensive analyses of gene structure and function. We cross-referenced 28.5K individual loci in the rice genome defined by mapping of 578K FL-cDNA clones with the 56K loci predicted in the TIGR genome assembly. Based on the annotation status and the presence of corresponding cDNA clones, genes were classified into 23K annotated expressed (AE) genes, 33K annotated non-expressed (ANE) genes, and 5.5K non-annotated expressed (NAE) genes. We developed a 60mer oligo-array for analysis of gene expression from each locus. Analysis of gene structures and expression levels revealed that the general features of gene structure and expression of NAE and ANE genes were considerably different from those of AE genes. The results also suggested that the cloning efficiency of rice FL-cDNA is associated with the transcription activity of the corresponding genetic locus, although other factors may also have an effect. Comparison of the coverage of FL-cDNA among gene families suggested that FL-cDNA from genes encoding rice- or eukaryote-specific domains, and those involved in regulatory functions were difficult to produce in bacterial cells. Collectively, these results indicate that rice genes can be divided into distinct groups based on transcription activity and gene structure, and that the coverage bias of FL-cDNA clones exists due to the incompatibility of certain eukaryotic genes in bacteria

Functional annotation of human long noncoding RNAs via molecular phenotyping

Long noncoding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes, and yet, their functions remain largely unknown. As part of the FANTOM6 project, we systematically knocked down the expression of 285 lncRNAs in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNAs exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest-todate lncRNA knockdown data set with molecular phenotyping (over 1000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.Peer reviewe

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism

The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome.

X chromosomes are unusual in many regards, not least of which is their nonrandom gene content. The causes of this bias are commonly discussed in the context of sexual antagonism and the avoidance of activity in the male germline. Here, we examine the notion that, at least in some taxa, functionally biased gene content may more profoundly be shaped by limits imposed on gene expression owing to haploid expression of the X chromosome. Notably, if the X, as in primates, is transcribed at rates comparable to the ancestral rate (per promoter) prior to the X chromosome formation, then the X is not a tolerable environment for genes with very high maximal net levels of expression, owing to transcriptional traffic jams. We test this hypothesis using The Encyclopedia of DNA Elements (ENCODE) and data from the Functional Annotation of the Mammalian Genome (FANTOM5) project. As predicted, the maximal expression of human X-linked genes is much lower than that of genes on autosomes: on average, maximal expression is three times lower on the X chromosome than on autosomes. Similarly, autosome-to-X retroposition events are associated with lower maximal expression of retrogenes on the X than seen for X-to-autosome retrogenes on autosomes. Also as expected, X-linked genes have a lesser degree of increase in gene expression than autosomal ones (compared to the human/Chimpanzee common ancestor) if highly expressed, but not if lowly expressed. The traffic jam model also explains the known lower breadth of expression for genes on the X (and the Z of birds), as genes with broad expression are, on average, those with high maximal expression. As then further predicted, highly expressed tissue-specific genes are also rare on the X and broadly expressed genes on the X tend to be lowly expressed, both indicating that the trend is shaped by the maximal expression level not the breadth of expression per se. Importantly, a limit to the maximal expression level explains biased tissue of expression profiles of X-linked genes. Tissues whose tissue-specific genes are very highly expressed (e.g., secretory tissues, tissues abundant in structural proteins) are also tissues in which gene expression is relatively rare on the X chromosome. These trends cannot be fully accounted for in terms of alternative models of biased expression. In conclusion, the notion that it is hard for genes on the Therian X to be highly expressed, owing to transcriptional traffic jams, provides a simple yet robustly supported rationale of many peculiar features of X's gene content, gene expression, and evolution