The tuatara (Sphenodon punctatus)-the only living member of the reptilian order Rhynchocephalia (Sphenodontia), once widespread across Gondwana 1,2-is an iconic species that is endemic to New Zealand 2,3. A key link to the now-extinct stem reptiles (from which dinosaurs, modern reptiles, birds and mammals evolved), the tuatara provides key insights into the ancestral amniotes 2,4. Here we analyse the genome of the tuatara, which-at approximately 5 Gb-is among the largest of the vertebrate genomes yet assembled. Our analyses of this genome, along with comparisons with other vertebrate genomes, reinforce the uniqueness of the tuatara. Phylogenetic analyses indicate that the tuatara lineage diverged from that of snakes and lizards around 250 million years ago. This lineage also shows moderate rates of molecular evolution, with instances of punctuated evolution. Our genome sequence analysis identifies expansions of proteins, non-protein-coding RNA families and repeat elements, the latter of which show an amalgam of reptilian and mammalian features. The sequencing of the tuatara genome provides a valuable resource for deep comparative analyses of tetrapods, as well as for tuatara biology and conservation. Our study also provides important insights into both the technical challenges and the cultural obligations that are associated with genome sequencing.

IgG–IgM immunochromatographic strip for rapid screening of SARS-CoV-2 infection including confirmed patients, suspect and asymptomatic carriers in 15 min.

Background: Hepatocellular carcinoma (HCC) is the most common liver cancer and the mechanisms of hepatocarcinogenesis remain elusive. Objective: This study aims to mine hub genes associated with HCC using multiple databases. Methods: Data sets GSE45267, GSE60502, GSE74656 were downloaded from GEO database. Differentially expressed genes (DEGs) between HCC and control in each set were identified by limma software. The GO term and KEGG pathway enrichment of the DEGs aggregated in the datasets (aggregated DEGs) were analyzed using DAVID and KOBAS 3.0 databases. Protein-protein interaction (PPI) network of the aggregated DEGs was constructed using STRING database. GSEA software was used to verify the biological process. Association between hub genes and HCC prognosis was analyzed using patients’ information from TCGA database by survminer R package. Results: From GSE45267, GSE60502 and GSE74656, 7583, 2349, and 553 DEGs were identified respectively. A total of 221 aggregated DEGs, which were mainly enriched in 109 GO terms and 29 KEGG pathways, were identified. Cell cycle phase, mitotic cell cycle, cell division, nuclear division and mitosis were the most significant GO terms. Metabolic pathways, cell cycle, chemical carcinogenesis, retinol metabolism and fatty acid degradation were the main KEGG pathways. Nine hub genes (TOP2A, NDC80, CDK1, CCNB1, KIF11, BUB1, CCNB2, CCNA2 and TTK) were selected by PPI network and all of them were associated with prognosis of HCC patients. Conclusion: TOP2A, NDC80, CDK1, CCNB1, KIF11, BUB1, CCNB2, CCNA2 and TTK were hub genes in HCC, which may be potential biomarkers of HCC and targets of HCC therapy.

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The relationship between genetic variation and gene expression in individual brain cell types and subtypes has remained elusive. Here, we generated single-nucleus RNA sequencing data from the dorsolateral prefrontal cortex of 424 individuals of advanced age; analyzing 1.5 million nuclear transcriptomes, we assessed the effect of genetic variants on RNA expression incis(cis-eQTL) for 7 cell types and 81 cell subtypes. This effort identified 10,004 eGenes at the cell type level and 8,138 eGenes at the cell subtype level. Many eGenes are only detected within cell subtypes. A new variant influencesAPOEexpression only in microglia and is associated with greater cerebral amyloid angiopathy but not Alzheimer pathology, accounting for the effect ofAPOEε4, providing mechanistic insights into both pathologies. While eQTLs are readily detected, only aTMEM106Bvariant robustly affects the proportion of cell subtypes. Integration of these results with GWAS highlighted the targeted cell type and likely causal gene within susceptibility loci for Alzheimer's, Parkinson's, schizophrenia, and educational attainment.

Input-output model on cement plants were established. Carbon dioxide emissions of key steps and carbon footprint of products were calculated and predicted using the input-output model. The results showed that CO2 emission in the plant (the production of the plant is 1320000t a year) reached 910000 t a year and CO2 emission per ton product is 0.689 ton. Over 80% of the total CO2 was emitted during the process of firing，so the firing process is the key step for reducing CO2 emission in the cement plant. Carbon footprint of three kinds of cement products including ordinary portland cement, portland pozzolan cement and portland blast furnace slag cement are 0.76, 0.59, 0.72 respectively.

A key goal of aging research was to understand mechanisms underlying healthy aging and develop methods to promote the human healthspan. One approach is to identify gene regulations unique to healthy aging compared with aging in the general population (i.e., “common” aging). Here, we leveraged Genotype‐Tissue Expression (GTEx) project data to investigate “healthy” and “common” aging gene expression regulations at a tissue level in humans and their interconnection with diseases. Using GTEx donors' disease annotations, we defined a “healthy” aging cohort for each tissue. We then compared the age‐associated genes derived from this cohort with age‐associated genes from the “common” aging cohort which included all GTEx donors; we also compared the “healthy” and “common” aging gene expressions with various disease‐associated gene expressions to elucidate the relationships among “healthy,” “common” aging and disease. Our analyses showed that 1. GTEx “healthy” and “common” aging shared a large number of gene regulations; 2. Despite the substantial commonality, “healthy” and “common” aging genes also showed distinct function enrichment, and “common” aging genes had a higher enrichment for disease genes; 3. Disease‐associated gene regulations were overall different from aging gene regulations. However, for genes regulated by both, their regulation directions were largely consistent, implying some aging processes could increase the susceptibility to disease development; and 4. Possible protective mechanisms were associated with some “healthy” aging gene regulations. In summary, our work highlights several unique features of GTEx “healthy” aging program. This new knowledge could potentially be used to develop interventions to promote the human healthspan.

BackgroundTransposable elements (TEs) are primarily responsible for the DNA losses and gains in genome sequences that occur over time within and between species. TEs themselves evolve, with clade specific LTR/ERV, LINEs and SINEs responsible for the bulk of species-specific genomic features. Because TEs can contain regulatory motifs, they can be exapted as regulators of gene expression. While TE insertions can provide evolutionary novelty for the regulation of gene expression, their overall impact on the evolution of gene expression is unclear. Previous investigators have shown that tissue specific gene expression in amniotes is more similar across species than within species, supporting the existence of conserved developmental gene regulation. In order to understand how species-specific TE insertions might affect the evolution/conservation of gene expression, we have looked at the association of gene expression in six tissues with TE insertions in six representative amniote genomes.ResultsA novel bootstrapping approach has been used to minimise the conflation of effects of repeat types on gene expression. We compared the expression of orthologs containing recent TE insertions to orthologs that contained older TE insertions, and the expression of non-orthologs containing recent TE insertions to non-orthologs with older TE insertions. Both orthologs and non-orthologs showed significant differences in gene expression associated with TE insertions. TEs were found associated with species-specific changes in gene expression, and the magnitude and direction of expression changes were noteworthy. Overall, orthologs containing species-specific TEs were associated with lower gene expression, while in non-orthologs, non-species specific TEs were associated with higher gene expression. Exceptions were SINE elements in human and chicken, which had an opposite association with gene expression compared to other species.ConclusionsOur observed species-specific associations of TEs with gene expression support a role for TEs in speciation/response to selection by species. TEs do not exhibit consistent associations with gene expression and observed associations can vary depending on the age of TE insertions. Based on these observations, it would be prudent to refrain from extrapolating these and previously reported associations to distantly related species.Electronic supplementary materialThe online version of this article (10.1186/s13100-018-0124-5) contains supplementary material, which is available to authorized users.