The complex hexaploid oil‐Camellia genome traces back its phylogenomic history and multi‐omics analysis of Camellia oil biosynthesis

Summary: Oil‐Camellia (Camellia oleifera), belonging to the Theaceae family Camellia, is an important woody edible oil tree species. The Camellia oil in its mature seed kernels, mainly consists of more than 90% unsaturated fatty acids, tea polyphenols, flavonoids, squalene and other active substances, which is one of the best quality edible vegetable oils in the world. However, genetic research and molecular breeding on oil‐Camellia are challenging due to its complex genetic background. Here, we successfully report a chromosome‐scale genome assembly for a hexaploid oil‐Camellia cultivar Changlin40. This assembly contains 8.80 Gb genomic sequences with scaffold N50 of 180.0 Mb and 45 pseudochromosomes comprising 15 homologous groups with three members each, which contain 135 868 genes with an average length of 3936 bp. Referring to the diploid genome, intragenomic and intergenomic comparisons of synteny indicate homologous chromosomal similarity and changes. Moreover, comparative and evolutionary analyses reveal three rounds of whole‐genome duplication (WGD) events, as well as the possible diversification of hexaploid Changlin40 with diploid occurred approximately 9.06 million years ago (MYA). Furthermore, through the combination of genomics, transcriptomics and metabolomics approaches, a complex regulatory network was constructed and allows to identify potential key structural genes (SAD, FAD2 and FAD3) and transcription factors (AP2 and C2H2) that regulate the metabolism of Camellia oil, especially for unsaturated fatty acids biosynthesis. Overall, the genomic resource generated from this study has great potential to accelerate the research for the molecular biology and genetic improvement of hexaploid oil‐Camellia, as well as to understand polyploid genome evolution

Identification and Verification of Molecular Subtypes with Enhanced Immune Infiltration Based on m6A Regulators in Cutaneous Melanoma

Background. As the most aggressive type of skin cancer, cutaneous melanoma (CM) is experiencing a rapidly rising mortality in recent years. Exploring potential prognostic biomarkers or mechanisms of disease progression therefore has a great significance for CM. The purpose of this study was to identify genetic markers and prognostic performance of N6-methyladenosine (m6A) regulators in CM. Method. Gene expression profiles, copy number variation (CNV), and single nucleotide polymorphism (SNP) data of patients were obtained from The Cancer Genome Atlas (TCGA) database. Results. Genomic variation and association analysis of gene expressions revealed a high degree of genomic variation in the presence of m6A-regulated genes. m6A patients with high-frequency genomic variants in the regulatory gene tended to develop a worse prognosis (p<0.01). Unsupervised cluster analysis of the expression profiles of m6A-regulated genes identified three clinically distinct molecular subtypes, including degradation-enhanced subgroup and immune-enhanced subgroup, with significant prognostic differences (p=0.046). A novel prognostic signature, which was established according to m6A-related characteristic genes identified through genome-wide expression spectrum, could effectively identify samples with poor prognosis and enhanced immune infiltration, and the effectiveness was also verified in the dataset of the chip. Conclusion. We identified genetic changes in the m6A regulatory gene in CM and related survival outcomes. The findings of this study provide new insights into the epigenetic understanding of m6A in CM

Quasi-monoenergetic carbon ions generation from a double-layer target driven by extreme laser pulses

High quality energetic carbon ions produced via laser-plasma have many applications in tumor therapy, fast ignition and warm dense matter generation. However, the beam achieved in current experiments is still limited by either a large energy spread or a low peak energy. In this paper, a hybrid scheme for the generation of quasi-monoenergetic carbon ions is proposed by an ultra-intense laser pulse irradiating a double-layer target. Multi-dimensional particle-in-cell (PIC) simulations show that the carbon ions are first accelerated via laser piston mechanism in the former carbon layer and then further accelerated by Coulomb repulsion force in the attached neon target. Since electrons are bunched synchronously in longitudinal and transverse direction by radiation reaction during the whole acceleration process, a quasi-monoenergetic carbon ion beam is eventually produced. In the following stage, the neon target provides the Coulomb field required for the continuous acceleration of the carbon ions which helps to prevent the carbon ion layer from diffusion. It is demonstrated that quasi-monoenergetic carbon ions with peak energy of 465 MeV u ^−1 , energy spread of ∼13%, a divergence of ∼15 ^∘ , and laser-to-ion energy conversion of 20% can be achieved by using a laser pulse with intensity of 1.23 × 10 ^23 W cm ^−2 . An analytical model is also proposed to interpret the carbon ion acceleration, which is fairly consistent with the PIC simulations

Guidebook for Using the Tool BEST Cement: Benchmarking and Energy Savings Tool for the Cement Industry

The Benchmarking and Energy Savings Tool (BEST) Cement is a process-based tool based on commercially available efficiency technologies used anywhere in the world applicable to the cement industry. This version has been designed for use in China. No actual cement facility with every single efficiency measure included in the benchmark will likely exist; however, the benchmark sets a reasonable standard by which to compare for plants striving to be the best. The energy consumption of the benchmark facility differs due to differences in processing at a given cement facility. The tool accounts for most of these variables and allows the user to adapt the model to operational variables specific for his/her cement facility. Figure 1 shows the boundaries included in a plant modeled by BEST Cement. In order to model the benchmark, i.e., the most energy efficient cement facility, so that it represents a facility similar to the user's cement facility, the user is first required to input production variables in the input sheet (see Section 6 for more information on how to input variables). These variables allow the tool to estimate a benchmark facility that is similar to the user's cement plant, giving a better picture of the potential for that particular facility, rather than benchmarking against a generic one. The input variables required include the following: (1) the amount of raw materials used in tonnes per year (limestone, gypsum, clay minerals, iron ore, blast furnace slag, fly ash, slag from other industries, natural pozzolans, limestone powder (used post-clinker stage), municipal wastes and others); the amount of raw materials that are preblended (prehomogenized and proportioned) and crushed (in tonnes per year); (2) the amount of additives that are dried and ground (in tonnes per year); (3) the production of clinker (in tonnes per year) from each kiln by kiln type; (4) the amount of raw materials, coal and clinker that is ground by mill type (in tonnes per year); (5) the amount of production of cement by type and grade (in tonnes per year); (6) the electricity generated onsite; and, (7) the energy used by fuel type; and, the amount (in RMB per year) spent on energy. The tool offers the user the opportunity to do a quick assessment or a more detailed assessment--this choice will determine the level of detail of the energy input. The detailed assessment will require energy data for each stage of production while the quick assessment will require only total energy used at the entire facility (see Section 6 for more details on quick versus detailed assessments). The benchmarking tool provides two benchmarks--one for Chinese best practices and one for international best practices. Section 2 describes the differences between these two and how each benchmark was calculated. The tool also asks for a target input by the user for the user to set goals for the facility

Applying 1H NMR Spectroscopy to Detect Changes in the Urinary Metabolite Levels of Chinese Half-Pipe Snowboarders after Different Exercises

Monitoring physical training is important for the health and performance of athletes, and real-time assessment of fatigue is crucial to improve training efficiency. The relationship between key biomarkers and exercise has been reported. The aim of this study was to determine the effects of different levels of training exercises on the urine metabolome. 1H NMR-based metabolomics analysis was performed on urine samples from half-pipe snowboarders, and spectral profiles were subjected to PCA and PLS-DA. Our results show that metabolic profiles varied during different stages of exercises. Lactate, alanine, trimethylamine, malonate, taurine, and glycine levels decreased while TMAO and phenylalanine levels increased in the stage with higher amount and intensity of exercise. Although the amount of exercise was reduced in subsequent stage, no significant variations of metabolic profile were found. Metabolic changes induced by training level were analyzed with related metabolic pathway. Studying metabolome changes can provide a better understanding of the physiology of athletes and could aid in adjusting training

Highly Efficient Genome Editing Using Geminivirus-Based CRISPR/Cas9 System in Cotton Plant

Upland cotton (Gossypium hirsutum), an allotetraploid, contains At- and Dt- subgenome and most genes have multiple homologous copies, which pose a huge challenge to investigate genes’ function due to the functional redundancy. Therefore, it is of great significance to establish effective techniques for the functional genomics in cotton. In this study, we tested two novel genome editing vectors and compared them with the CRISPR/Cas9 system (pRGEB32-GhU6.7) developed in our laboratory previously. In the first new vector, the sgRNA transcription unite was constructed into the replicon (LIR-Donor-SIR-Rep-LIR) of the bean yellow dwarf virus (BeYDV) and named as pBeYDV-Cas9-KO and in the second vector, the ubiquitin promoter that drives Cas9 protein was replaced with a constitutive CaMV 35S promoter and defined as pRGEB32-35S. The results from transgenic cotton calli/plants revealed that pBeYDV-Cas9-KO vector showed the highest editing efficiency of GhCLA1 in At and Dt subgenomes edited simultaneously up to 73.3% compared to the 44.6% of pRGEB32-GhU6.7 and 51.2% of pRGEB32-35S. The editing efficiency of GhCLA1 in At and Dt subgenome by pBeYDV-Cas9-KO was 85.7% and 97.2%, respectively, whereas the efficiency by pRGEB32-GhU6.7 and pRGEB32-35S vectors was 67.7%, 86.5%, 84%, and 87.2%, respectively. The editing profile of pBeYDV-Cas9-KO was mainly composed of fragment deletion, accounting for 84.0% and ranging 1–10 bp in length. The main editing sites are located at positions 11–17 upstream of PAM site. The off-target effects were not detected in all potential off-target sites. Taken together, the pBeYDV-Cas9-KO system has high editing efficiency and specificity with wide editing range than the traditional CRISPR/Cas9 system, which provides a powerful tool for cotton functional genomics research and molecular breeding

Development Status and Strategies of Xieka

In this paper, the present situation of Xieka cattle was investigated, and the body size of Xieka cattle was measured. It was found that there were some problems in Xieka cattle, such as backward feeding and management, and degradation of breeds. The corresponding strategies were put forward in order to promote the resource protection, development and utilization of Xieka cattle

Hierarchical Self-Assembled Polyimide Microspheres Functionalized with Amidoxime Groups for Uranium-Containing Wastewater Remediation

Through molecule self-assembly and subsequent surface functionalization, novel uranium adsorbent AO–OB hierarchical self-assembled polyimide microspheres (AO-OBHSPIMs) were obtained by introducing the amidoxime groups into hierarchical self-assembled polyimide microspheres for the efficient and selective recovery of uranium from wastewater. The results of Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), X-ray diffraction (XRD), and nitrogen adsorption–desorption isotherm showed that AO-OBHSPIMs were a semicrystalline polymer material with self-supporting hierarchical structure and low pore volume, and they were equipped with abundant amidoxime groups. Given the recognized selectivity of amidoxime groups and their hierarchical structure, AO-OBHSPIMs exhibited excellent selectivity to uranyl ions. Moreover, AO-OBHSPIMs exhibited good stability and recyclability and remarkable removal percentage within low-concentration solution (99.4%) and simulated uranium-containing wastewater (97.3%). AO-OBHSPIMs could be applied to fixed-bed column adsorption due to their large particle size and self-supporting hierarchical structure that can facilitate water flow. The in-depth discussion of the adsorption mechanism showed that the adsorption mainly depended on the combined action of electrostatic interactions and complexation, and the adsorption process was a spontaneous endothermic monolayer adsorption. In summary, AO-OBHSPIMs exhibited good application prospects in uranium-containing wastewater remediation

Runs of Homozygosity Analysis Reveals Genomic Diversity and Population Structure of an Indigenous Cattle Breed in Southwest China

In aiming to achieve sustainable development goals in the livestock industry, it is becoming increasingly necessary and important for the effective conservation of genetic resources. There are some indigenous cattle breeds in Sichuan, southwest China, for which, however, the genetic diversity and population structures still remain unknown because of the unavailability of systematic breeding programs and pedigree information. Xieka cattle are an indigenous breed locally distributed in southeastern Sichuan and have a long-term evolutionary adaptation to local environments and climates. In this study, we obtained 796,828 single nucleotide polymorphisms (SNPs) through sequencing the genomes of 30 Xieka cattle and used them for analyzing the genetic diversity and runs of homozygosity (ROH). The mean nucleotide diversity was 0.28 and 72% of SNPs were found to be in the heterozygous states. A total of 4377 ROH were detected with even distribution among all autosomes, and 74% of them were lower than 1 Mb in length. Meanwhile, only five ROH were found longer than 5 Mb. We further determined 19 significant genomic regions that were obviously enriched by ROH, in which 35 positional candidate genes were found. Some of these genes have been previously reported to be significantly associated with various production traits in cattle, such as meat quality, carcass performances, and diseases. In conclusion, the relatively high degree of genetic diversity of Xieka cattle was revealed using the genomic information, and the proposed candidate genes will help us optimize the breeding programs regarding this indigenous breed