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Rationale & Objective: The Kidney Failure Risk Equations have been proven to perform well in multinational databases, whereas validation in Asian populations is lacking. This study sought to externally validate the equations in a community-based chronic kidney disease cohort in China. Study Design: A retrospective cohort study. Setting & Participants: Patients with and estimated glomerular filtration rate (eGFR)

Breeding for nitrogen use efficiency (NUE) is becoming more important as global uncertainty makes the production and application of nitrogen (N) fertilizers more expensive and environmentally unfriendly. Despite this, most cereal breeding programs still use yield-related components as proxies for NUE, likely due to the prohibitive cost and time of collecting and analyzing samples through traditional lab-based methods. Drone-based NUE phenotyping provides a viable and scalable alternative as it is quicker, non-destructive, and consistent. Here, we present a study that utilized financially accessible cost-effective drones mounted with red-green-blue (RGB) image sensors coupled with the open-source AirMeasurer platform and advanced statistical analysis to exclude low-NUE lines in multi-seasonal field experiments. The method helped us to identify high N agronomic use efficiency lines but was less effective with a high N recovery efficiency line. We found that the drone-powered approach was very effective at 180 kg N per hectare (N180, an optimized N-rate) as it completely removed low-NUE wheat lines in the trial, which would facilitate breeders to quickly reduce the number of lines taken through multi-year breeding programs. Hence, this encouraging and scalable approach demonstrates its ability to conduct NUE phenotyping in wheat. With continuous refinements in field experiments, this method would be employable as an openly accessible platform to identify NUE lines at different N-rates for breeding and resource use efficiency studies in wheat.

Inefficient nitrogen (N) utilization in agricultural production has led to many negative impacts such as excessive use of N fertilizers, redundant plant growth, greenhouse gases, long-lasting toxicity in ecosystem, and even effect on human health, indicating the importance to optimize N applications in cropping systems. Here, we present a multiseasonal study that focused on measuring phenotypic changes in wheat plants when they were responding to different N treatments under field conditions. Powered by drone-based aerial phenotyping and the AirMeasurer platform, we first quantified 6 N response-related traits as targets using plot-based morphological, spectral, and textural signals collected from 54 winter wheat varieties. Then, we developed dynamic phenotypic analysis using curve fitting to establish profile curves of the traits during the season, which enabled us to compute static phenotypes at key growth stages and dynamic phenotypes (i.e., phenotypic changes) during N response. After that, we combine 12 yield production and N-utilization indices manually measured to produce N efficiency comprehensive scores (NECS), based on which we classified the varieties into 4 N responsiveness (i.e., N-dependent yield increase) groups. The NECS ranking facilitated us to establish a tailored machine learning model for N responsiveness-related varietal classification just using N-response phenotypes with high accuracies. Finally, we employed the Wheat55K SNP Array to map single-nucleotide polymorphisms using N response-related static and dynamic phenotypes, helping us explore genetic components underlying N responsiveness in wheat. In summary, we believe that our work demonstrates valuable advances in N response-related plant research, which could have major implications for improving N sustainability in wheat breeding and production.

Immune cell changes are associated with Kawasaki disease (KD) pathogenesis. Here, using single cell RNA sequencing of PBMC, the authors show monocyte inflammatory genes are over-expressed in KD and TCR and BCR clonotype sequences show oligoclonal expansions after intravenous immunoglobulin therapy.

Relational keyword search (R-KWS) systems provide users with a convenient means in relational database queries. There exist two main types of R-KWS: those based on Data Graphs and those based on Schema Graphs. In this paper, we focus on the latter, R-KWS based on Schema Graphs. Most existing methods are typically inefficient due to the large number of repetitive operation caused by overlapping candidate networks and the execution of lots of complex queries. We present the R-KWS approach based on combined candidate network evaluation to improve the query efficiency. The proposed Combined Candidate Network (CCN) can efficiently share the overlapping part between candidate networks, and then avoid the repetitive operation during the evaluation of candidate networks. Meanwhile, CCN possesses another important characteristic that candidate networks within a CCN are still identifiable after candidate networks being compressed into a CCN. We design an algorithm based on this characteristic to evaluate CCN for the generation of final query results. This algorithm is able to eliminate the execution of a large number of complex queries required by most existing approaches, and thus significantly improve the efficiency of keyword search. Experiments on real datasets show that our approach can improve query efficiency without any loss of the quality of query results with respect to existing approaches.

Abstract Background Sheep have developed the ability to store fat in their tails, which is a unique way of reserving energy to survive a harsh environment. However, the mechanism underlying this adaptive trait remains largely unsolved. Results In the present study, we provide evidence for the genetic determinants of fat tails, based on whole genome sequences of 89 individual sheep. A genome-wide scan of selective sweep identified several candidate loci including a region at chromosome 13, a haplotype of which underwent rapid evolution and spread through fat-tailed populations in China and the Middle East. Sequence analysis revealed an inter-genic origin of this locus, which later became a hotspot of ruminant-specific retro-transposon named BovB. Additionally, the candidate locus was validated based on a fat- and thin-tailed cross population. The expression of an upstream gene BMP2 was differentially regulated between fat-tailed and thin-tailed individuals in tail adipose and several other tissue types. Conclusions Our findings suggest the fixation of fat tails in domestic sheep is caused by a selective sweep near a retro-transposable hotspot at chromosome 13, the diversity of which specifically affects the expression of BMP2. The present study has shed light onto the understanding of fat metabolism.

Abstract Background Hepatocellular carcinoma (HCC) is the one of the most common cancers and lethal diseases in the world. DNA methylation alteration is frequently observed in HCC and may play important roles in carcinogenesis and diagnosis. Methods Using the TCGA HCC dataset, we classified HCC patients into different methylation subtypes, identified differentially methylated and expressed genes, and analyzed cis- and trans-regulation of DNA methylation and gene expression. To find potential diagnostic biomarkers for HCC, we screened HCC-specific CpGs by comparing the methylation profiles of 375 samples from HCC patients, 50 normal liver samples, 184 normal blood samples, and 3780 samples from patients with other cancers. A logistic regression model was constructed to distinguish HCC patients from normal controls. Model performance was evaluated using three independent datasets (including 327 HCC samples and 122 normal samples) and ten newly collected biopsies. Results We identified a group of patients with a CpG island methylator phenotype (CIMP) and found that the overall survival of CIMP patients was poorer than that of non-CIMP patients. Our analyses showed that the cis-regulation of DNA methylation and gene expression was dominated by the negative correlation, while the trans-regulation was more complex. More importantly, we identified six HCC-specific hypermethylated sites as potential diagnostic biomarkers. The combination of six sites achieved ~ 92% sensitivity in predicting HCC, ~ 98% specificity in excluding normal livers, and ~ 98% specificity in excluding other cancers. Compared with previously published methylation markers, our markers are the only ones that can distinguish HCC from other cancers. Conclusions Overall, our study systematically describes the DNA methylation characteristics of HCC and provides promising biomarkers for the diagnosis of HCC.

Abstract Hepatitis B virus (HBV) is classified into several genotypes, correlated with different geographic distributions, clinical outcomes and susceptible human populations. It is crucial to investigate the evolutionary significance behind the diversification of HBV genotypes, because it improves our understanding of their pathological differences and pathogen-host interactions. Here, we performed comprehensive analysis of HBV genome sequences collected from public database. With a stringent criteria, we generated a dataset of 2992 HBV genomes from eight major genotypes. In particular, we applied a specified classification of non-synonymous and synonymous variants in overlapping regions, to distinguish joint and independent gene evolutions. We confirmed the presence of selective constraints over non-synonymous variants in consideration of overlapping regions. We then performed the McDonald-Kreitman test and revealed adaptive evolutions of non-synonymous variants during genotypic differentiation. Remarkably, we identified strong positive selection that drove the differentiation of PreS1 domain, which is an essential regulator involved in viral transmission. Our study presents novel evidences for the adaptive evolution of HBV genotypes, which suggests that these viruses evolve directionally for maintenance or improvement of successful infections.

IntroductionChronic kidney disease (CKD) is an important public health problem worldwide. However, there are few active disease surveillance systems for it. The China Kidney Disease Network (CK-NET) was established as a comprehensive surveillance system for CKD using various data sources. As part of this, the proposed CK-NET-Yinzhou study aims to build a regional surveillance system in a developed coastal area in China to obtain detailed dynamic information about kidney disease and to improve the ability to manage the disease effectively.Methods and analysisYinzhou is a district of Ningbo city, Zhejiang province. The district has a population of more than 1 million. By 2016, 98% were registered in a regional health information system that started in 2009. This system includes administrative databases containing general demographic characteristics, health check information, inpatient and outpatient electronic medical records, health insurance information, disease surveillance and management information, and death certificates. We will use longitudinal individual electronic health record data to identify people with CKD by repeated laboratory measurements and diagnostic codes. We will also evaluate the associated risk factors, prognosis and disease management. An intelligent clinical decision support system (CDSS) will be developed based on clinical guidelines, domain expert knowledge and real-world data, and will be integrated into the hospital information system.Ethics and disseminationThe CK-NET-Yinzhou study has been reviewed and approved by the Peking University First Hospital Ethics Committee. Privacy of local residents registered with the health information system will be tightly protected through the study process. The findings of the study will be disseminated through peer-reviewed journal articles, posters and presentations in national and international scientific conferences, as well as among local practitioners through the CDSS.

Shading created by intercropping reduces the photosynthetic capacity of soybean plants but also directly affects the pod setting process of soybean. However, which of the changed aspects induce the yield differences in intercropped soybean cultivars is still unknown. Four soybean cultivars with similar yield and growth and development processes in monoculture were selected by a pre-experiment. Field experiments were carried out from 2015 to 2017 to investigate the leaf photosynthetic parameters, total biomass, reproductive characteristics, yield and yield components of soybean. The yield of soybean cultivars was significantly decreased in intercropping systems and the yield of cultivars (cvs.) ZH39 and QH34 were considerably higher than those of cvs. HD19 and HD20. Besides, the pod and seed number and harvest index were also reduced by intercropping and the yield components of cvs. ZH39 and QH34 in intercropping were significantly higher than those of cvs. HD19 and HD20, other than the seed size. Although the parameters of leaf photosynthetic capacity (leaf area index, net photosynthetic rate, and chlorophyll content) of soybean were changed by intercropping, there was no significant difference among cultivars. Additionally, the CGRR1−R5 (crop growth rate between R1 and R5) of intercropped soybean was lower than that of monoculture, while no significant differences were observed in different cultivars. The reproductive biomass at R5 was significantly different among soybean cultivars, and the reproductive partitioning and seed set efficiency of different cultivars were varied by the reproductive biomass at R5. Therefore, high-yielding cultivars in intercropping can achieve higher yield due to more reproductive structures survived at R5.

Primary duck hepatocytes (PDH) displays differential susceptibility to duck hepatitis B virus when maintained in the media supplemented with fetal bovine serum or dimethyl sulfoxide (DMSO) which has been widely used for the maintenance of hepatocytes, and prolonging susceptibility to hepadnavirus. However the mechanism underlying maintenance of susceptibility to hepadnavirus by DMSO treatment remains unclear. In this study, a global transcriptome analysis of PDHs under different culture conditions was conducted for investigating the effects of DMSO on maintenance of susceptibility of PDH to DHBV in vitro. The 384 differential expressed genes (DEGs) were identified by comparisons between each library pair (PDHs cultured with or without DMSO or fresh isolated PDH). We analyzed canonical pathways in which the DEGs were enriched in Hepatic Fibrosis / Hepatic Stellate Cell Activation, Bile Acid Biosynthesis and Tight Junction signaling. After re-annotation against human genome data, the 384 DEGs were pooled together with proteins belonging to hepatitis B pathway to construct a protein-protein interaction network. The combination of decreased expression of liver-specific genes (CYP3A4, CYP1E1, CFI, RELN and GSTA1 et al) with increased expression of hepatocyte-dedifferentiation-associated genes (PLA2G4A and PLCG1) suggested that in vitro culture conditions results in the fading of hepatocyte phenotype in PDHs. The expression of seven DEGs associated with tight junction formation (JAM3, PPP2R2B, PRKAR1B, PPP2R2C, MAGI2, ACTA2 and ACTG2) was up-regulated after short-term culture in vitro, which was attenuated in the presence of DMSO. Those results could shed light on DHBV infection associated molecular events affected by DMSO.

Patient-derived xenograft (PDX) tumor model is a powerful technology in evaluating anti-cancer drugs and facilitating personalized medicines. Multiple research centers and commercial companies have put huge efforts into building PDX mouse models. However, PDX models have not been widely available and their molecular features have not been systematically characterized. In this study, we provided a comprehensive survey of PDX transcriptome by integrating analysis of 58 patients involving 8 different tumors. The median correlation coefficient between patients and xenografts is 0.94, which is higher than that between patients and cell line panel or between patients with the same tumor. Major differential gene expressions in PDX occur in the engraftment of human tumor tissue into mice, while gene expressions are relatively stable over passages. 48 genes are frequently differentially expressed in PDX mice of multiple cancers. They are enriched in extracellular matrix and immune response, and some are reported as targets for anticancer drugs. A simulation study showed that expression change between PDX and patient tumor (6%) would result in acceptable change in drug sensitivity (3%). Our findings demonstrate that PDX mice represent the gene-expression and drug-response features of primary tumors effectively, and it is recommended to monitoring the overall expression profiles and drug target genes in clinical application.

The Goto-Kakizaki (GK) rat, which has been developed by repeated inbreeding of glucose-intolerant Wistar rats, is the most widely studied rat model for Type 2 diabetes (T2D). However, the detailed genetic background of T2D phenotype in GK rats is still largely unknown. We report a survey of T2D susceptible variations based on high-quality whole genome sequencing of GK and Wistar rats, which have generated a list of GK-specific variations (228 structural variations, 2660 CNV amplification and 2834 CNV deletion, 1796 protein affecting SNVs or indels) by comparative genome analysis and identified 192 potential T2D-associated genes. The genes with variants are further refined with prior knowledge and public resource including variant polymorphism of rat strains, protein-protein interactions and differential gene expression. Finally we have identified 15 genetic mutant genes which include seven known T2D related genes (Tnfrsf1b, Scg5, Fgb, Sell, Dpp4, Icam1, and Pkd2l1) and eight high-confidence new candidate genes (Ldlr, Ccl2, Erbb3, Akr1b1, Pik3c2a, Cd5, Eef2k, and Cpd). Our result reveals that the T2D phenotype may be caused by the accumulation of multiple variations in GK rat, and that the mutated genes may affect biological functions including adipocytokine signaling, glycerolipid metabolism, PPAR signaling, T cell receptor signaling and insulin signaling pathways. We present the genomic difference between two closely related rat strains (GK and Wistar) and narrow down the scope of susceptible loci. It also requires further experimental study to understand and validate the relationship between our candidate variants and T2D phenotype. Our findings highlight the importance of sequenced-based comparative genomics for investigating disease susceptibility loci in inbreeding animal models.

Salvia miltiorrhiza Bunge, a perennial plant of Lamiaceae, accumulates abietane-type diterpenoids of tanshinones in root, which have been used as traditional Chinese medicine to treat neuroasthenic insomnia and cardiovascular diseases. However, to date the biosynthetic pathway of tanshinones is only partially elucidated and the mechanism for their root-specific accumulation remains unknown. To identify enzymes and transcriptional regulators involved in the biosynthesis of tanshinones, we conducted transcriptome profiling of S. miltiorrhiza root and leaf tissues using the 454 GS-FLX pyrosequencing platform, which generated 550,546 and 525,292 reads, respectively. RNA sequencing reads were assembled and clustered into 64,139 unigenes (29,883 isotigs and 34,256 singletons). NCBI non-redundant protein databases (NR) and Swiss-Prot database searches anchored 32,096 unigenes (50%) with functional annotations based on sequence similarities. Further assignments with Gene Ontology (GO) terms and KEGG biochemical pathways identified 168 unigenes referring to the terpenoid backbone biosynthesis (including 144 MEP and MVA pathway genes and 24 terpene synthases). Comparative analysis of the transcriptomes identified 2,863 unigenes that were highly expressed in roots, including those encoding enzymes of early steps of tanshinone biosynthetic pathway, such as copalyl diphosphate synthase (SmCPS), kaurene synthase-like (SmKSL) and CYP76AH1. Other differentially expressed unigenes predicted to be related to tanshinone biosynthesis fall into cytochrome P450 monooxygenases, dehydrogenases and reductases, as well as regulatory factors. In addition, 21 P450 genes were selectively confirmed by real-time PCR. Thus we have generated a large unigene dataset which provides a valuable resource for further investigation of the radix development and biosynthesis of tanshinones.

After traumatic injury, peripheral nerves can spontaneously regenerate through highly sophisticated and dynamic processes that are regulated by multiple cellular elements and molecular factors. Despite evidence of morphological changes and of expression changes of a few regulatory genes, global knowledge of gene expression changes and related biological processes during peripheral nerve injury and regeneration is still lacking. Here we aimed to profile global mRNA expression changes in proximal nerve segments of adult rats after sciatic nerve transection. According to DNA microarray analysis, the huge number of genes was differentially expressed at different time points (0.5 h-14 d) post nerve transection, exhibiting multiple distinct temporal expression patterns. The expression changes of several genes were further validated by quantitative real-time RT-PCR analysis. The gene ontology enrichment analysis was performed to decipher the biological processes involving the differentially expressed genes. Collectively, our results highlighted the dynamic change of the important biological processes and the time-dependent expression of key regulatory genes after peripheral nerve injury. Interestingly, we, for the first time, reported the presence of olfactory receptors in sciatic nerves. Hopefully, this study may provide a useful platform for deeply studying peripheral nerve injury and regeneration from a molecular-level perspective.

Lactobacillus delbrueckii subsp. bulgaricus (Lb. bulgaricus) is an important species of Lactic Acid Bacteria (LAB) used for cheese and yogurt fermentation. The genome of Lb. bulgaricus 2038, an industrial strain mainly used for yogurt production, was completely sequenced and compared against the other two ATCC collection strains of the same subspecies. Specific physiological properties of strain 2038, such as lysine biosynthesis, formate production, aspartate-related carbon-skeleton intermediate metabolism, unique EPS synthesis and efficient DNA restriction/modification systems, are all different from those of the collection strains that might benefit the industrial production of yogurt. Other common features shared by Lb. bulgaricus strains, such as efficient protocooperation with Streptococcus thermophilus and lactate production as well as well-equipped stress tolerance mechanisms may account for it being selected originally for yogurt fermentation industry. Multiple lines of evidence suggested that Lb. bulgaricus 2038 was genetically closer to the common ancestor of the subspecies than the other two sequenced collection strains, probably due to a strict industrial maintenance process for strain 2038 that might have halted its genome decay and sustained a gene network suitable for large scale yogurt production.

Unlike the central nervous system, peripheral nerves can regenerate when damaged. MicroRNA (miRNA) is a novel class of small, non-coding RNA that regulates gene expression at the post-transcriptional level. Here, we report regular alterations of miRNA expression following rat sciatic nerve injury using deep sequencing. We harvested dorsal root ganglia tissues and the proximal stumps of the nerve, and identified 201 and 225 known miRNAs with significant expression variance at five time points in these tissues after sciatic nerve transaction, respectively. Subsequently, hierarchical clustering, miRNA expression pattern and co-expression network were performed. We screened out specific miRNAs and further obtained the intersection genes through target analysis software (Targetscan and miRanda). Moreover, GO and KEGG enrichment analyses of these intersection genes were performed. The bioinformatics analysis indicated that the potential targets for these miRNAs were involved in nerve regeneration, including neurogenesis, neuron differentiation, vesicle-mediated transport, homophilic cell adhesion and negative regulation of programmed cell death that were known to play important roles in regulating nerve repair. Finally, we combined differentially expressed mRNA with the predicted targets for selecting inverse miRNA-target pairs. Our results show that the abnormal expression of miRNA may contribute to illustrate the molecular mechanisms of nerve regeneration and that miRNAs are potential targets for therapeutic interventions and may enhance intrinsic regenerative ability.

Efforts in phylogenomics have greatly improved our understanding of the backbone tree of life. However, due to the systematic error in sequence data, a sequence-based phylogenomic approach leads to well-resolved but statistically significant incongruence. Thus, independent test of current phylogenetic knowledge is required. Here, we have devised a distance-based strategy to reconstruct a highly resolved backbone tree of life, on the basis of the genome context networks of 195 fully sequenced representative species. Along with strongly supporting the monophylies of three superkingdoms and most taxonomic sub-divisions, the derived tree also suggests some intriguing results, such as high G+C gram positive origin of Bacteria, classification of Symbiobacterium thermophilum and Alcanivorax borkumensis in Firmicutes. Furthermore, simulation analyses indicate that addition of more gene relationships with high accuracy can greatly improve the resolution of the phylogenetic tree. Our results demonstrate the feasibility of the reconstruction of highly resolved phylogenetic tree with extensible gene networks across all three domains of life. This strategy also implies that the relationships between the genes (gene network) can define what kind of species it is.

The evolution of new gene families subsequent to gene duplication may be coupled to the fluctuation of population and environment variables. Based upon that, we presented a systematic analysis of the animal transmembrane gene duplication events on a macroevolutionary scale by integrating the palaeontology repository. The age of duplication events was calculated by maximum likelihood method, and the age distribution was estimated by density histogram and normal kernel density estimation. We showed that the density of the duplicates displays a positive correlation with the estimates of maximum number of cell types of common ancestors, and the oxidation events played a key role in the major transitions of this density trace. Next, we focused on the Phanerozoic phase, during which more macroevolution data are available. The pulse mass extinction timepoints coincide with the local peaks of the age distribution, suggesting that the transmembrane gene duplicates fixed frequently when the environment changed dramatically. Moreover, a 61-million-year cycle is the most possible cycle in this phase by spectral analysis, which is consistent with the cycles recently detected in biodiversity. Our data thus elucidate a strong coupling of duplication events and macroevolution; furthermore, our method also provides a new way to address these questions.