Development and evaluation of the first high-throughput SNP array for common carp (Cyprinus carpio)

BACKGROUND: A large number of single nucleotide polymorphisms (SNPs) have been identified in common carp (Cyprinus carpio) but, as yet, no high-throughput genotyping platform is available for this species. C. carpio is an important aquaculture species that accounts for nearly 14% of freshwater aquaculture production worldwide. We have developed an array for C. carpio with 250,000 SNPs and evaluated its performance using samples from various strains of C. carpio. RESULTS: The SNPs used on the array were selected from two resources: the transcribed sequences from RNA-seq data of four strains of C. carpio, and the genome re-sequencing data of five strains of C. carpio. The 250,000 SNPs on the resulting array are distributed evenly across the reference C.carpio genome with an average spacing of 6.6 kb. To evaluate the SNP array, 1,072 C. carpio samples were collected and tested. Of the 250,000 SNPs on the array, 185,150 (74.06%) were found to be polymorphic sites. Genotyping accuracy was checked using genotyping data from a group of full-siblings and their parents, and over 99.8% of the qualified SNPs were found to be reliable. Analysis of the linkage disequilibrium on all samples and on three domestic C.carpio strains revealed that the latter had the longer haplotype blocks. We also evaluated our SNP array on 80 samples from eight species related to C. carpio, with from 53,526 to 71,984 polymorphic SNPs. An identity by state analysis divided all the samples into three clusters; most of the C. carpio strains formed the largest cluster. CONCLUSIONS: The Carp SNP array described here is the first high-throughput genotyping platform for C. carpio. Our evaluation of this array indicates that it will be valuable for farmed carp and for genetic and population biology studies in C. carpio and related species

Signal Reconstruction of Compressed Sensing Based on Alternating Direction Method of Multipliers

AbstractThe sparse signal reconstruction of compressive sensing can be accomplished by $l_1$-norm minimization, but in many existing algorithms, there are the problems of low success probability and high computational complexity. To overcome these problems, an algorithm based on the alternating direction method of multipliers is proposed. First, using variable splitting techniques, an additional variable is introduced, which is tied to the original variable via an affine constraint. Then, the problem is transformed into a non-constrained optimization problem by means of the augmented Lagrangian multiplier method, where the multipliers can be obtained using the gradient ascent method according to dual optimization theory. The $l_1$-norm minimization can finally be solved by cyclic iteration with concise form, where the solution of the original variable could be obtained by a projection operator, and the auxiliary variable could be solved by a soft threshold operator. Simulation results show that a higher signal reconstruction success probability is obtained when compared to existing methods, while a low computational cost is required.Abstract The sparse signal reconstruction of compressive sensing can be accomplished by $l_1$-norm minimization, but in many existing algorithms, there are the problems of low success probability and high computational complexity. To overcome these problems, an algorithm based on the alternating direction method of multipliers is proposed. First, using variable splitting techniques, an additional variable is introduced, which is tied to the original variable via an affine constraint. Then, the problem is transformed into a non-constrained optimization problem by means of the augmented Lagrangian multiplier method, where the multipliers can be obtained using the gradient ascent method according to dual optimization theory. The $l_1$-norm minimization can finally be solved by cyclic iteration with concise form, where the solution of the original variable could be obtained by a projection operator, and the auxiliary variable could be solved by a soft threshold operator. Simulation results show that a higher signal reconstruction success probability is obtained when compared to existing methods, while a low computational cost is required

Optimizing nitrogen and phosphorus application to improve soil organic carbon and alfalfa hay yield in alfalfa fields

Soil organic carbon (SOC) is the principal factor contributing to enhanced soil fertility and also functions as the major carbon sink within terrestrial ecosystems. Applying fertilizer is a crucial agricultural practice that enhances SOC and promotes crop yields. Nevertheless, the response of SOC, active organic carbon fraction and hay yield to nitrogen and phosphorus application is still unclear. The objective of this study was to investigate the impact of nitrogen-phosphorus interactions on SOC, active organic carbon fractions and hay yield in alfalfa fields. A two-factor randomized group design was employed in this study, with two nitrogen levels of 0 kg·ha-1 (N0) and 120 kg·ha-1 (N1) and four phosphorus levels of 0 kg·ha-1 (P0), 50 kg·ha-1 (P1), 100 kg·ha-1 (P2) and 150 kg·ha-1 (P3). The results showed that the nitrogen and phosphorus treatments increased SOC, easily oxidized organic carbon (EOC), dissolved organic carbon (DOC), particulate organic carbon (POC), microbial biomass carbon (MBC) and hay yield in alfalfa fields, and increased with the duration of fertilizer application, reaching a maximum under N1P2 or N1P3 treatments. The increases in SOC, EOC, DOC, POC, MBC content and hay yield in the 0–60 cm soil layer of the alfalfa field were 9.11%-21.85%, 1.07%-25.01%, 6.94%-22.03%, 10.36%-44.15%, 26.46%-62.61% and 5.51%-23.25% for the nitrogen and phosphorus treatments, respectively. The vertical distribution of SOC, EOC, DOC and POC contents under all nitrogen and phosphorus treatments was highest in the 0–20 cm soil layer and tended to decrease with increasing depth of the soil layer. The MBC content was highest in the 10–30 cm soil layer. DOC/SOC, MBC/SOC (excluding N0P1 treatment) and POC/SOC were all higher in the 0–40 cm soil layer of the alfalfa field compared to the N0P0 treatment, indicating that the nitrogen and phosphorus treatments effectively improved soil fertility, while EOC/SOC and DOC/SOC were both lower in the 40–60 cm soil layer than in the N0P0 treatment, indicating that the nitrogen and phosphorus treatments improved soil carbon sequestration potential. The soil layer between 0-30 cm exhibited the highest sensitivity index for MBC, whereas the soil layer between 30-60 cm had the highest sensitivity index for POC. This suggests that the indication for changes in SOC due to nitrogen and phosphorus treatment shifted from MBC to POC as the soil depth increased. Meanwhile, except the 20–30 cm layer of soil in the N0P1 treatment and the 20–50 cm layer in the N1P0 treatment, all fertilizers enhanced the soil Carbon management index (CMI) to varying degrees. Structural equation modeling shows that nitrogen and phosphorus indirectly affect SOC content by changing the content of the active organic carbon fraction, and that SOC is primarily impacted by POC and MBC. The comprehensive assessment indicated that the N1P2 treatment was the optimal fertilizer application pattern. In summary, the nitrogen and phosphorus treatments improved soil fertility in the 0–40 cm soil layer and soil carbon sequestration potential in the 40–60 cm soil layer of alfalfa fields. In agroecosystems, a recommended application rate of 120 kg·ha-1 for nitrogen and 100 kg·ha-1 for phosphorus is the most effective in increasing SOC content, soil carbon pool potential and alfalfa hay yield

A Drive to Driven Model of Mapping Intraspecific Interaction Networks.

Community ecology theory suggests that an individual\u27s phenotype is determined by the phenotypes of its coexisting members to the extent at which this process can shape community evolution. Here, we develop a mapping theory to identify interaction quantitative trait loci (QTL) governing inter-individual dependence. We mathematically formulate the decision-making strategy of interacting individuals. We integrate these mathematical descriptors into a statistical procedure, enabling the joint characterization of how QTL drive the strengths of ecological interactions and how the genetic architecture of QTL is driven by ecological networks. In three fish full-sib mapping experiments, we identify a set of genome-wide QTL that control a range of societal behaviors, including mutualism, altruism, aggression, and antagonism, and find that these intraspecific interactions increase the genetic variation of body mass by about 50%. We showcase how the interaction QTL can be used as editors to reconstruct and engineer new social networks for ecological communities

Torque Optimization of a Seven-Phase Bi-harmonic PMSM in Healthy and Degraded Mode

Compared to sinusoidal machines, a bi-harmonic machine (with only two harmonics of similar value in the electromotive force spectrum) can develop torque of comparable values under three kinds of supply: with only first or both first and third sinusoidal currents. Therefore, more degrees of freedom for the control of the machine can be achieved. In this paper, the specificities of a 7-phase bi-harmonic permanent magnet synchronous machine (PMSM) are investigated under different control strategies, such as maximum torque per ampere (MTPA) at low speed and fluxweakening strategies at high speed, both in healthy and faulty operation modes. The fault with one open-circuited phase are taken into account. The current references are calculated in order to maximize the output torque under the constraint on both voltage and current. The performances of the considered machine is validated by numerical results

LncRNA LIMp27 Regulates the DNA Damage Response through p27 in p53‐Defective Cancer Cells

P53 inactivation occurs in about 50% of human cancers, where p53-driven p21 activity is devoid and p27 becomes essential for the establishment of the G1/S checkpoint upon DNA damage. Here, this work shows that the E2F1-responsive lncRNA LIMp27 selectively represses p27 expression and contributes to proliferation, tumorigenicity, and treatment resistance in p53-defective colon adenocarcinoma (COAD) cells. LIMp27 competes with p27 mRNA for binding to cytoplasmically localized hnRNA0, which otherwise stabilizes p27 mRNA leading to cell cycle arrest at the G0/G1 phase. In response to DNA damage, LIMp27 is upregulated in both wild-type and p53-mutant COAD cells, whereas cytoplasmic hnRNPA0 is only increased in p53-mutant COAD cells due to translocation from the nucleus. Moreover, high LIMp27 expression is associated with poor survival of p53-mutant but not wild-type p53 COAD patients. These results uncover an lncRNA mechanism that promotes p53-defective cancer pathogenesis and suggest that LIMp27 may constitute a target for the treatment of such cancers

Research on Value Stream Analysis of Prefabricated Building Based on SVN

With the adjustment of the national industrial structure, the transformation of the production mode of the construction industry and the advocacy of the concept of green and energy-saving building, prefabricated building will become the next trend of the construction industry. However, prefabricated building has not been popularized in China's construction industry, which may attribute to the participating parties have not realized the value-added effect that brought by the application of prefabricated building. Therefore, it is necessary to analyze the value gained by all parties in the application of prefabricated building from a global and systematic perspective. Based on the theory of Value and Stakeholders Value Network (SVN) methods, this paper may build a network with value – information – coordination of the stakeholders in a prefabricated building project, and make a comprehensive evaluation on the value acquisition ability and the uncertain risks of key stakeholders in a prefabricated building projects, which may provide a new perspective for the implementation and decision-making of prefabricated building projects

Research on Value Stream Analysis of Prefabricated Building Based on SVN

With the adjustment of the national industrial structure, the transformation of the production mode of the construction industry and the advocacy of the concept of green and energy-saving building, prefabricated building will become the next trend of the construction industry. However, prefabricated building has not been popularized in China's construction industry, which may attribute to the participating parties have not realized the value-added effect that brought by the application of prefabricated building. Therefore, it is necessary to analyze the value gained by all parties in the application of prefabricated building from a global and systematic perspective. Based on the theory of Value and Stakeholders Value Network (SVN) methods, this paper may build a network with value – information – coordination of the stakeholders in a prefabricated building project, and make a comprehensive evaluation on the value acquisition ability and the uncertain risks of key stakeholders in a prefabricated building projects, which may provide a new perspective for the implementation and decision-making of prefabricated building projects.</jats:p