Dynamic transcriptional and chromatin accessibility landscape of medaka embryogenesis.

Medaka (Oryzias latipes) has become an important vertebrate model widely used in genetics, developmental biology, environmental sciences, and many other fields. A high-quality genome sequence and a variety of genetic tools are available for this model organism. However, existing genome annotation is still rudimentary, as it was mainly based on computational prediction and short-read RNA-seq data. Here we report a dynamic transcriptome landscape of medaka embryogenesis profiled by long-read RNA-seq, short-read RNA-seq, and ATAC-seq. By integrating these data sets, we constructed a much-improved gene model set including about 17,000 novel isoforms and identified 1600 transcription factors, 1100 long noncoding RNAs, and 150,000 potential cis-regulatory elements as well. Time-series data sets provided another dimension of information. With the expression dynamics of genes and accessibility dynamics of cis-regulatory elements, we investigated isoform switching, as well as regulatory logic between accessible elements and genes, during embryogenesis. We built a user-friendly medaka omics data portal to present these data sets. This resource provides the first comprehensive omics data sets of medaka embryogenesis. Ultimately, we term these three assays as the minimum ENCODE toolbox and propose the use of it as the initial and essential profiling genomic assays for model organisms that have limited data available. This work will be of great value for the research community using medaka as the model organism and many others as well.

Regulation of P300 and HDAC1 on endoplasmic reticulum stress in isoniazid-induced HL-7702 hepatocyte injury.

P300 and HDAC1 can be involved in the development of various liver diseases by regulating gene transcription. Endoplasmic reticulum stress (ERS) is one of the main pathways of apoptosis and is activated during inflammatory responses, but the roles of P300 and HDAC1 in ERS in antituberculosis drug-induced liver injury (ADLI) are not clear. This study confirms that isoniazid can change the states of P300 and HDAC1 in HL-7702 hepatocyte metabolism and induce ERS, causing hepatocyte injury and apoptosis. When combined with C646, however, P300 can be reduced. HL-7702 cells were flattened, and the cytoplasm became crinkled. To a certain extent, ERS was relieved, but hepatocytes suffered worse damage, and the rate of cell apoptosis markedly increased. When MS-275 was applied, HDAC1 level was increased, cell fusion appeared, and fluorescence intensity of endoplasmic reticulum was weakened. In addition, ERS was aggravated, but liver injury was relieved, and the apoptosis rate significantly decreased. Therefore, alteration of P300 and HDAC1 status and ERS are involved in ADLI, and changes in P300 and HDAC1 can regulate ERS and then affect cell damage.

Task Allocation Model Based on Worker Friend Relationship for Mobile Crowdsourcing.

With the rapid development of mobile devices, mobile crowdsourcing has become an important research focus. According to the task allocation, scholars have proposed many methods. However, few works discuss combining social networks and mobile crowdsourcing. To maximize the utilities of mobile crowdsourcing system, this paper proposes a task allocation model considering the attributes of social networks for mobile crowdsourcing system. Starting from the homogeneity of human beings, the relationship between friends in social networks is applied to mobile crowdsourcing system. A task allocation algorithm based on the friend relationships is proposed. The GeoHash coding mechanism is adopted in the process of calculating the strength of worker relationship, which effectively protects the location privacy of workers. Utilizing synthetic dataset and the real-world Yelp dataset, the performance of the proposed task allocation model was evaluated. Through comparison experiments, the effectiveness and applicability of the proposed allocation mechanism were verified.

Independent regulation of gene expression level and noise by histone modifications.

The inherent stochasticity generates substantial gene expression variation among isogenic cells under identical conditions, which is frequently referred to as gene expression noise or cell-to-cell expression variability. Similar to (average) expression level, expression noise is also subject to natural selection. Yet it has been observed that noise is negatively correlated with expression level, which manifests as a potential constraint for simultaneous optimization of both. Here, we studied expression noise in human embryonic cells with computational analysis on single-cell RNA-seq data and in yeast with flow cytometry experiments. We showed that this coupling is overcome, to a certain degree, by a histone modification strategy in multiple embryonic developmental stages in human, as well as in yeast. Importantly, this epigenetic strategy could fit into a burst-like gene expression model: promoter-localized histone modifications (such as H3K4 methylation) are associated with both burst size and burst frequency, which together influence expression level, while gene-body-localized ones (such as H3K79 methylation) are more associated with burst frequency, which influences both expression level and noise. We further knocked out the only "writer" of H3K79 methylation in yeast, and observed that expression noise is indeed increased. Consistently, dosage sensitive genes, such as genes in the Wnt signaling pathway, tend to be marked with gene-body-localized histone modifications, while stress responding genes, such as genes regulating autophagy, tend to be marked with promoter-localized ones. Our findings elucidate that the "division of labor" among histone modifications facilitates the independent regulation of expression level and noise, extend the "histone code" hypothesis to include expression noise, and shed light on the optimization of transcriptome in evolution.

An Incentive Mechanism in Mobile Crowdsourcing Based on Multi-Attribute Reverse Auctions.

In order to avoid malicious competition and select high quality crowd workers to improve the utility of crowdsourcing system, this paper proposes an incentive mechanism based on the combination of reverse auction and multi-attribute auction in mobile crowdsourcing. The proposed online incentive mechanism includes two algorithms. One is the crowd worker selection algorithm based on multi-attribute reverse auction that adopts dynamic threshold to make an online decision for whether accept a crowd worker according to its attributes. Another is the payment determination algorithm which determines payment for a crowd worker based on its reputation and quality of sensing data, that is, a crowd worker can get payment equal to the bidding price before performing task only if his reputation reaches good reputation threshold, otherwise he will get payment based on his data sensing quality. We prove that our proposed online incentive mechanism has the properties of computational efficiency, individual rationality, budget-balance, truthfulness and honesty. Through simulations, the efficiency of our proposed online incentive mechanism is verified which can improve the efficiency, adaptability and trust degree of the mobile crowdsourcing system.

Optimizing Retransmission Threshold in Wireless Sensor Networks.

The retransmission threshold in wireless sensor networks is critical to the latency of data delivery in the networks. However, existing works on data transmission in sensor networks did not consider the optimization of the retransmission threshold, and they simply set the same retransmission threshold for all sensor nodes in advance. The method did not take link quality and delay requirement into account, which decreases the probability of a packet passing its delivery path within a given deadline. This paper investigates the problem of finding optimal retransmission thresholds for relay nodes along a delivery path in a sensor network. The object of optimizing retransmission thresholds is to maximize the summation of the probability of the packet being successfully delivered to the next relay node or destination node in time. A dynamic programming-based distributed algorithm for finding optimal retransmission thresholds for relay nodes along a delivery path in the sensor network is proposed. The time complexity is O n Δ · max 1 ≤ i ≤ n { u i } , where u i is the given upper bound of the retransmission threshold of sensor node i in a given delivery path, n is the length of the delivery path and Δ is the given upper bound of the transmission delay of the delivery path. If Δ is greater than the polynomial, to reduce the time complexity, a linear programming-based ( 1 + p m i n ) -approximation algorithm is proposed. Furthermore, when the ranges of the upper and lower bounds of retransmission thresholds are big enough, a Lagrange multiplier-based distributed O ( 1 ) -approximation algorithm with time complexity O ( 1 ) is proposed. Experimental results show that the proposed algorithms have better performance.

Truthful Incentive Mechanisms for Social Cost Minimization in Mobile Crowdsourcing Systems.

With the emergence of new technologies, mobile devices are capable of undertaking computational and sensing tasks. A large number of users with these mobile devices promote the formation of the Mobile Crowdsourcing Systems (MCSs). Within a MCS, each mobile device can contribute to the crowdsourcing platform and get rewards from it. In order to achieve better performance, it is important to design a mechanism that can attract enough participants with mobile devices and then allocate the tasks among participants efficiently. In this paper, we are interested in the investigation of tasks allocation and price determination in MCSs. Two truthful auction mechanisms are proposed for different working patterns. A Vickrey-Clarke-Groves (VCG)-based auction mechanism is proposed to the continuous working pattern, and a suboptimal auction mechanism is introduced for the discontinuous working pattern. Further analysis shows that the proposed mechanisms have the properties of individual rationality and computational efficiencies. Experimental results suggest that both mechanisms guarantee all the mobile users bidding with their truthful values and the optimal maximal social cost can be achieved in the VCG-based auction mechanism.

Near-Infrared-II-Activatable Self-Assembled Manganese Porphyrin-Gold Heterostructures for Photoacoustic Imaging-Guided Sonodynamic-Augmented Photothermal/Photodynamic Therapy.

Porphyrins and their derivatives are widely used as photosensitizers and sonosensitizers in tumor treatment. Nevertheless, their poor water solubility and low chemical stability reduce their singlet oxygen (1O2) yield and, consequently, their photodynamic therapy (PDT) and sonodynamic therapy (SDT) efficiency. Although strategies for porphyrin molecule assembly have been developed to augment 1O2 generation, there is scope for further improving PDT and SDT efficiencies. Herein, we synthesized ordered manganese porphyrin (SM) nanoparticles with well-defined self-assembled metalloporphyrin networks that enabled efficient energy transfer for enhanced photocatalytic and sonocatalytic activity in 1O2 production. Subsequently, Au nanoparticles were grown in situ on the SM surface by anchoring the terminal alkynyl of porphyrin to form plasmonic SMA heterostructures, which showed the excellent near-infrared-II (NIR-II) region absorption and photothermal properties, and facilitated electron-hole pair separation and transfer. With the modification of hyaluronic acid (HA), SMAH heterostructure nanocomposites exhibited good water solubility and were actively targeted to cancer cells. Under NIR-II light and ultrasound (US) irradiation, the SMAH generates hyperthermia, and a large amount of 1O2, inducing cancer cell damage. Both in vitro and in vivo studies confirmed that the SMAH nanocomposites effectively suppressed tumor growth by decreasing GSH levels in SDT-augmented PDT/PTT. Moreover, by utilizing the strong absorption in the NIR-II window, SMAH nanocomposites can achieve NIR-II photoacoustic imaging-guided combined cancer treatment. This work provides a paradigm for enhancing the 1O2 yield of metalloporphyrins to improve the synergistic therapeutic effect of SDT/PDT/PTT.

Epidemic Vulnerability Index for Effective Vaccine Distribution against Pandemic.

COVID-19 vaccine distribution route directly impacts the community's mortality and infection rate. Therefore, optimal vaccination dissemination would appreciably lower the death and infection rates. This paper proposes the Epidemic Vulnerability Index (EVI) that quantitatively evaluates the subject's potential risk. Our primary aim for the suggested index is to diminish both infection rate and death rate efficiently. EVI was accordingly designed with clinical factors determining the mortality and social factors incorporating the infection rate. Through statistical COVID-19 patient dataset analysis and social network analysis with an agent-based model that is analogous to a real-world system, we define and experimentally validate the capability of EVI. Our experiments consist of nine vaccination distribution scenarios, including existing indexes which estimate the risk and stochastically proliferate the contagion and vaccine in a 300,000 agent-based graph network. We compared the outcome and variation of the three metrics in the experiments: infection case, death case, and death rate. Through this assessment, vaccination by the descending order of EVI has shown to have a significant outcome with an average of 5.0% lower infection cases, 9.4% lower death cases, and 3.5% lower death rate than other vaccine distribution routes.

Case report: A homozygous ADAMTSL2 missense variant causes geleophysic dysplasia with high similarity to Weill-Marchesani syndrome.

Background: Geleophysic dysplasia and Weill-Marchesani syndrome from the acromelic dysplasias group of genetic skeletal disorders share remarkable clinical and genetic overlap. Methods: Ophthalmological, physical, radiological examinations were conducted with a female patient in her early 30 s. Whole exome sequencing followed by Sanger sequencing validation was performed to identify the genetic cause. Results: The patient, born to consanguineous Chinese parents, presented with microspherophakia, lens subluxation, high myopia, short statue, small hands and feet, stiff joints, and thickened skin. A diagnosis of Weill-Marchesani syndrome was initially made for her. However, genetic testing reveals that the patient is homozygous for the c.1966G>A (p.Gly656Ser) variant in ADAMTSL2, and that the patient's healthy mother and daughter are heterozygous for the variant. As mutations in ADAMTSL2 are known to cause autosomal recessive geleophysic dysplasia, the patient is re-diagnosed with geleophysic dysplasia in terms of her genotype and phenotype. Conclusion: The present study describes the clinical phenotype of the homozygous ADAMTSL2 p. Gly656Ser variant, which increases our understanding of the genotype-phenotype correlation in acromelic dysplasias.

Inference Attacks and Controls on Genotypes and Phenotypes for Individual Genomic Data.

The rapid growth of DNA-sequencing technologies motivates more personalized and predictive genetic-oriented services, which further attract individuals to increasingly release their genome information to learn about personalized medicines, disease predispositions, genetic compatibilities, etc. Individual genome information is notoriously privacy-sensitive and highly associated with relatives. In this paper, we present an inference attack algorithm to predict target genotypes and phenotypes based on belief propagation in factor graphs. With this algorithm, an attacker can effectively predict the target genotypes and phenotypes of target individuals based on genome information shared by individuals or their relatives, and genotype and phenotype association from genome-wide association study (GWAS). To address the privacy threats resulted from such inference attacks, we elaborate the metrics to evaluate data utility and privacy and then present a data sanitization method. We evaluate our inference attack algorithm and data sanitization method on real GWAS dataset: Age-related macular degeneration (AMD) case/control dataset. The evaluation results show that our work can effectively defense against genome threats while guaranteeing data utility.

Decode-seq: a practical approach to improve differential gene expression analysis.

Many differential gene expression analyses are conducted with an inadequate number of biological replicates. We describe an easy and effective RNA-seq approach using molecular barcoding to enable profiling of a large number of replicates simultaneously. This approach significantly improves the performance of differential gene expression analysis. Using this approach in medaka (Oryzias latipes), we discover novel genes with sexually dimorphic expression and genes necessary for germ cell development. Our results also demonstrate why the common practice of using only three replicates in differential gene expression analysis should be abandoned.

SIRT1 alleviates isoniazid-induced hepatocyte injury by reducing histone acetylation in the IL-6 promoter region.

Silent information regulator 1 (SIRT1) is a type III histone deacetylase that is related to the inhibition of the inflammatory response. The aim of this study was to investigate the regulation of SIRT1 on isoniazid-induced hepatocyte injury and the possible mechanism of histone modification. We found that compared with the blank control group, expression of SIRT1 was decreased in the isoniazid group and that expression of NF-κB p65 was increased, leading to an increase of the expression of inflammatory cytokines Interleukin-6 (IL-6) and Tumour necrosis factor alpha (TNF-α). The level of histone H3K9 acetylation in the promoter region of IL-6 was increased as well. Addition of a SIRT1 agonist (SRT1720) alleviated the inflammatory reaction caused by isoniazid, while the use of a SIRT1 inhibitor (EX527) aggravated the inflammatory damage to cells. In conclusion, these findings indicated that during the period of isoniazid-induced hepatocyte injury, SIRT1 levels were decreased and inflammatory factor levels were increased. Activation of SIRT1 may reduce hepatocyte injury by reducing the level of histone H3K9 acetylation in the promoter region of the IL-6 gene.

Involvement of methylation of MicroRNA-122, -125b and -106b in regulation of Cyclin G1, CAT-1 and STAT3 target genes in isoniazid-induced liver injury.

BACKGROUND: This investigation aimed to evaluate the role of methylation in the regulation of microRNA (miR)-122, miR-125b and miR-106b gene expression and the expression of their target genes during isoniazid (INH)-induced liver injury. METHODS: Rats were given INH 50 mg kg- 1·d- 1 once per day for 3, 7, 10, 14, 21 and 28 days and were sacrificed. Samples of blood and liver were obtained. RESULTS: We analysed the methylation and expression levels of miR-122, miR-125b and miR-106b and their potential gene targets in livers. Liver tissue pathologies, histological scores and alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activities changed, indicating the occurrence of liver injury. Relative expression levels of miR-122, miR-125b and miR-106b genes in the liver decreased after INH administration and correlated with the scores of liver pathology and serum AST and ALT activities, suggesting that miR-122, miR-125b and miR-106b are associated with INH-induced liver injury. The amount of methylated miR-122, miR-125b and miR-106b in the liver increased after INH administration and correlated with their expression levels, suggesting the role of methylation in regulating miRNA gene expression. Two miR-122 gene targets, cell cycle protein G1 (Cyclin G1) and cationic amino acid transporter-1 (CAT-1), also increased at the mRNA and protein levels, which suggests that lower levels of miR-122 contribute to the upregulation of Cyclin G1 and CAT-1 and might play a role in INH-induced liver injury. Signal transducer and activator of transcription 3 (STAT3) was a common target gene of miR-125b and miR-106b, and its expression levels of mRNA and protein increased after INH administration. The protein expression of phosphorylated (p)-STAT3 and the mRNA expression of RAR-related orphan receptor gamma (RORγt) regulated by p-STAT3 also increased. Meanwhile, the mRNA and protein expression of interleukin (IL)-17 regulated by RORγt, and the mRNA and protein expression of CXCL1 and MIP-2 regulated by IL-17 increased after INH administration. These results demonstrate that lower levels of hepatic miR-125b and miR-106b contribute to the upregulation of STAT3 in stimulating the secretion of inflammatory factors during INH-induced liver injury. CONCLUSIONS: Our results suggested that DNA methylation probably regulates the expression of miRNA genes (miR-122, miR-125b, and miR-106b), affecting the expression of their gene targets (Cyclin G1, CAT-1, and STAT3) and participating in the process of INH-induced liver injury.

Involvement of histone hypoacetylation in INH-induced rat liver injury.

This study explores the mechanism of histone acetylation under the effect of oxidative stress in rat liver injury induced by isoniazid (INH). Fifty-six adult SD rats were selected and divided randomly into INH groups (48) and control (8). Rats in INH groups were intragastrically injected with 55 mg kg-1 day-1 for 3, 7, 10, 14, 21, and 28 days, and control rats were given an equal volume of distilled water. Pathological changes in liver tissues were observed by HE staining. Western blot analysis was conducted to measure the expression levels of H3k14ac and H4k8ac. The activities of HAT, HDAC and IL-1ß, and TNF-α were detected by ELISA in liver tissues. Real-time RT-PCR analysis was performed to determine the protein expression levels of HAT, HDAC, and IL-1ß and the mRNA expression of TNF-α. The levels of superoxide dismutase (SOD) and malondialdehyde (MDA) were assayed by biochemical methods in liver tissues. At different time points, the SOD activity decreased, whereas the MDA content significantly increased after 14 days (FSOD = 11.15, FMDA = 7.42, P < 0.01). During this period, the expression of histone acetylated H3K14 and H4K8 acetylation decreased compared with the control group (FH3K14 = 4.18, FH4K8 = 3.87, P < 0.05); by contrast, HDAC1 and HDAC2 showed a high expression level compared with those in the control group (FHDAC1 = 29.13, FHDAC2 = 58.34, P < 0.01). Moreover, the expression of CBP/P300 was lower than that in the control group (FCBP/P300 = 12.18, P = 0.001), and the protein contents of IL-1ß and TNF-α in rat liver tissues were up-regulated (FIL-1ß = 44.88, FTNF-α = 41.56, P < 0.01). These results suggest that histone acetylation is involved in INH-induced rat liver injury. Furthermore, the hypoacetylation of histones H3K14 and H4K8 is negatively correlated with oxidative stress-mediated rat liver injury.

Scheduling multi-task jobs with extra utility in data centers.

This paper investigates the problem of maximizing utility for job scheduling where each job consists of multiple tasks, each task has utility and each job also has extra utility if all tasks of that job are completed. We provide a 2-approximation algorithm for the single-machine case and a 2-approximation algorithm for the multi-machine problem. Both algorithms include two steps. The first step employs the Earliest Deadline First method to compute utility with only extra job utility, and it is proved that it obtains the optimal result for this sub-problem. The second step employs a Dynamic Programming method to compute utility without extra job utility, and it also derives the optimal result. An approximation result can then be obtained by combining the results of the two steps.

Statistical evaluation of NMR backbone resonance assignment.

This paper proposes a novel statistical evaluation model for automated protein NMR sequential resonance assignment. It can be bound to any assignment program and provides confidences for the whole output assignment and each individual mapping. A simulation study on a set of four proteins shows that the statistical evaluation results are informative.

Protein-protein interaction and group testing in bipartite graphs.

The interactions between bait proteins and prey proteins are often critical in many biological processes, such as the formation of macromolecular complexes and the transduction of signals in biological pathways. Thus, identifying all protein-protein interactions is an important task in those processes, which can be formulated as a group testing problem in bipartite graphs. In this paper, we take the advantages of the characteristics of bipartite graphs and present two nonadaptive algorithms for this problem. Furthermore, we illustrate a generalisation of our solution in a more general case.