OBJECTIVE: Roscoea is a Sino-Himalayan alpine genus in pantropical family Zingiberaeae. As traditional Tibetan medicinal plants, many species of this genus are threatened by digging, logging, land clearance, grazing and climate change. Roscoea debilis is an endemic species in the Hengduan Mountains with a narrow distribution range. In this study, the assembled and annotated genome of Roscoea was presented in order to furnish significant resources for comparative and functional genomic investigations. The first complete reference genome of Roscoea is expected to shed light on research on conservation and evolutionary biology.
METHODS: A chromosome-level genome of 1601.04 Mb was obtained for R. debilis by combining Illumina short reads (107.28 Gb) and PacBio Hi-Fi reads (64.08 Gb), achieving high-quality sequencing coverage of roughly 67 × and 40 ×. The assembly was additionally assisted by 271.65 Gb Hi-C data (169 ×), which resulted in a contig N50 of 136.17 Mb and a scaffold N50 of 90.48 Mb. Benchmarking Universal Single-Copy Orthologs (BUSCO) assessment results revealed that most of the core embryophyta genes (98.7%) in the BUSCO dataset (embryophyta_odb10) were successfully identified. Additionally, 96.44% of the genomic sequences were accurately mapped onto twelve pseudochromosomes.

BACKGROUND: Observational studies have shown that individual sleep traits habits are potential risk factors for major depression. However, it is not known whether there is a causal relationship between individual sleep traits habits such as continuous sleep duration, short sleep duration, short sleep duration, insomnia, nap during the day, snoring, and major depression. In this study, Mendelian randomization (MR) was used to predict major depressive disorder (MDD) in individuals sleep traits habits.
METHODS: Data were obtained from the genome-wide association study (GWAS). Nine MR analysis methods were used: Inverse Variance Weighted (IVW) [fixed effects/multiplicative random effects], simple mode, simple mode, weighted mode, simple median, weighted median, penalised weighted median, and MR-Egger, MR Egger (bootstrap). IVW was used as the main analysis method for the MR analysis of two samples, and the other methods were used as supplements.
RESULTS: The results obtained through the IVW method supported a causal relationship between sleep duration and decreased risk of MDD (odds ratio, ORivw: 0.998; 95 % CI: 0.996-0.999, P<0.001). Two-Sample MR, results showed that short sleep duration has a causal effect on the increased risk of MDD (odds ratio, ORivw: 1.179; 95 % CI: 1.108-1.255, P<0.001). However, there were no sufficient evidence supported that long sleep duration has a causal effect on the decreased risk of MDD (odds ratio, ORivw: 0.991; 95 % CI: 0.924-1.062, P = 0.793). A significant causal relationship between insomnia and increased risk of MDD was observed (OR: 1.233; 95 % CI: 1.214-1.253, P<0.001). Interestingly, our study also found that daytime napping has a causal effect on the increased risk of MDD (odds ratio, ORivw: 1.519; 95 % CI: 1.376-1.678, P<0.001). The present results did not show a significant causal relationship between snoring and the risk of MDD (ORivw: 1.000; 95 % CI: 0.998-1.002, P = 0.906). Obstructive sleep apnea (odds ratio, ORivw: 1.021; 95 % CI: 0.972-1.072, P = 0.407) and morning person (odds ratio, ORivw: 1.021; 95 % CI: 0.972-1.072, P = 0.407) have no causal effect on the increased risk of MDD.
CONCLUSIONS: The study could not ascertain whether there were genetic differences among different ethnicities, nations, and regions, as it only included participants of European ancestry.
CONCLUSIONS: In summary, our research provides genetic evidence for the relationship between individual sleep traits (short sleep duration, insomnia, daytime napping) and the increased risk of MDD. Interventions targeting lifestyle factors may reduce the risk of MDD.

This study investigated the effects of the nitrogen retention composite additives Ca(H2PO4)2 and MgSO4 on lignocellulose degradation, maturation, and fungal communities in composts. The study included control (C, without Ca(H2PO4)2 and MgSO4), 1% Ca(H2PO4)2 + 2% MgSO4 (CaPM1), 1.5% Ca(H2PO4)2 + 3% MgSO4 (CaPM2). The results showed that Ca(H2PO4)2 and MgSO4 enhanced the degradation of total organic carbon (TOC) and promoted the degradation of lignocellulose in compost, with CaPM2 showing the highest TOC and lignocellulose degradation. Changes in the three-dimensional excitation-emission matrix fluorescence spectroscopy (3D-EEM) of dissolved organic matter (DOM) components in compost indicated that the treatment group with the addition of Ca(H2PO4)2 and MgSO4 promoted the production of humic acids (HAs) and increased the degree of compost decomposition, with CaPM2 demonstrating the highest degree of decomposition. The addition of Ca(H2PO4)2 and MgSO4 modified the composition of the fungal community. Ca(H2PO4)2 and MgSO4 increased the relative abundance of Ascomycota, decreased unclassified_Fungi, and Glomeromycota, and activated the fungal genera Thermomyces and Aspergillus, which can degrade lignin and cellulose during the thermophilic stage of composting. Ca(H2PO4)2 and MgSO4 also increased the abundance of Saprotroph, particularly undefined Saprotroph. In conclusion, the addition of Ca(H2PO4)2 and MgSO4 in composting activated fungal communities involved in lignocellulose degradation, promoted the degradation of lignocellulose, and enhanced the maturation degree of compost.

OBJECTIVE: Brasenia is a monotypic genus in the family of Cabombaceae. The only species, B. schreberi, is a macrophyte distributed worldwide. Because it requires good water quality, it is endangered in China and other countries due to the deterioration of aquatic habitats. The young leaves and stems of B. schreberi are covered by thick mucilage, which has high medical value. As an allelopathic aquatic plant, it can also be used in the management of aquatic weeds. Here, we present its assembled and annotated genome to help shed light on medial and allelopathic substrates and facilitate their conservation.
METHODS: Genomic DNA and RNA extracted from B. schreberi leaf tissues were used for whole genome and RNA sequencing using a Nanopore and/or MGI sequencer. The assembly was 1,055,148,839 bp in length, with 92 contigs and an N50 of 22,379,495 bp. The repetitive elements in the assembly were 555,442,205 bp. A completeness assessment of the assembly with BUSCO and compleasm indicated 88.4 and 90.9% completeness in the Eudicots database and 95.4 and 96.6% completeness in the Embryphyta database. Gene annotation revealed 67,747 genes that coded for 73,344 proteins.

Cadmium (Cd)-contaminated soil poses a severe threat to crop production and human health, while also resulting in a waste of land resources. In this study, two types of organic fertilizer (ZCK: Low-content available iron; Z2: High-content available iron) were applied to Cd-contaminated soil for rice cultivation, and the effects of the fertilizer on rice growth and Cd passivation were investigated in conjunction with soil microbial analysis. Results showed that Z2 could alter the composition, structure, and diversity of microbial communities, as well as enhance the complexity and stability of the microbial network. Both 2% and 5% Z2 significantly increased the fresh weight and dry weight of rice plants while suppressing Cd absorption. The 2% Z2 exhibited the best Cd passivation effect. Gene predictions suggested that Z2 may promote plant growth by regulating microbial production of organic acids that dissolve phosphorus and potassium. Furthermore, it is suggested that Z2 may facilitate the absorption and immobilization of soil cadmium through the regulation of microbial cadmium efflux and uptake systems, as well as via the secretion of extracellular polysaccharides. In summary, Z2 can promote rice growth, suppress Cd absorption by rice, and passivate soil Cd by regulating soil microbial communities.

Seed sugar composition, mainly including fructose, glucose, sucrose, raffinose, and stachyose, is an important indicator of soybean [Glycine max (L.) Merr.] seed quality. However, research on soybean sugar composition is limited. To better understand the genetic architecture underlying the sugar composition in soybean seeds, we conducted a genome-wide association study (GWAS) using a population of 323 soybean germplasm accessions which were grown and evaluated under three different environments. A total of 31,245 single-nucleotide polymorphisms (SNPs) with minor allele frequencies (MAFs) ≥ 5% and missing data ≤ 10% were selected and used in the GWAS. The analysis identified 72 quantitative trait loci (QTLs) associated with individual sugars and 14 with total sugar. Ten candidate genes within the 100 Kb flanking regions of the lead SNPs across six chromosomes were significantly associated with sugar contents. According to GO and KEGG classification, eight genes were involved in the sugar metabolism in soybean and showed similar functions in Arabidopsis. The other two, located in known QTL regions associated with sugar composition, may play a role in sugar metabolism in soybean. This study advances our understanding of the genetic basis of soybean sugar composition and facilitates the identification of genes controlling this trait. The identified candidate genes will help improve seed sugar composition in soybean.

Lung cancer is the leading cause of cancer deaths globally, and lung adenocarcinoma (LUAD) is the most common type of lung cancer. Gene dysregulation plays an essential role in the development of LUAD. Drug repositioning based on associations between drug target genes and LUAD target genes are useful to discover potential new drugs for the treatment of LUAD, while also reducing the monetary and time costs of new drug discovery and development. Here, we developed a pipeline based on machine learning to predict potential LUAD-related target genes through established graph attention networks (GATs). We then predicted potential drugs for the treatment of LUAD through gene coincidence-based and gene network distance-based methods. Using data from 535 LUAD tissue samples and 59 precancerous tissue samples from The Cancer Genome Atlas, 48,597 genes were identified and used for the prediction model building of the GAT. The GAT model achieved good predictive performance, with an area under the receiver operating characteristic curve of 0.90. 1,597 potential LUAD-related genes were identified from the GAT model. These LUAD-related genes were then used for drug repositioning. The gene overlap and network distance with the target genes were calculated for 3,070 drugs and 672 preclinical compounds approved by the US Food and Drug Administration. At which, bromoethylamine was predicted as a novel potential preclinical compound for the treatment of LUAD, and cimetidine and benzbromarone were predicted as potential therapeutic drugs for LUAD. The pipeline established in this study presents new approach for developing targeted therapies for LUAD.

A magnetosome-producing bacterium Acidithiobacillus ferrooxidans BYM (At. ferrooxidans BYM) was isolated and magnetically screened. The magnetosome yield from 0.5896 to 13.1291 mg/g was achieved under different aeration rates, ferrous sulfate, ammonium sulfate, and gluconic acid concentrations at 30 ℃. TEM observed 6-9 magnetosomes in size of 20-80 nm irregularly dispersed in a cell. STEM-EDXS and HRTEM-FFT implied that the elongated-prismatic magnetite magnetosomes with {110} crystal faces grown along the [111] direction. Whole-genome sequencing and annotation of BYM showed that 3.2 Mb chromosome and 47.11 kb plasmid coexisted, and 322 genes associated with iron metabolism were discovered. Ten genes shared high similarity with magnetosome genes were predicted, providing sufficient evidence for the magnetosome-producing potential of BYM. Accordingly, we first proposed a hypothetic model of magnetosome formation including vesicle formation, iron uptake and mineralization, and magnetite crystal maturation in At. ferrooxidans. These indicated that At. ferrooxidans BYM would be used as a commercial magnetosome-producing microorganism.

CONCLUSIONS: In this first genetic study on assessing leaf thickness directly in cereals, major and environmentally stable QTL were detected in barley and candidate genes underlying a major locus were identified. Leaf thickness (LT) is an important characteristic affecting leaf functions which have been intensively studied. However, as LT has a small dimension in many plant species and technically difficult to measure, previous studies on this characteristic are often based on indirect estimations. In the first study of detecting QTL controlling LT by directly measuring the characteristic in barley, large and stable loci were detected from both field and glasshouse trials conducted in different cropping seasons by assessing a population of 201 recombinant inbred lines. Four loci (locating on chromosome arms 2H, 3H, 5H and 6H, respectively) were consistently detected for flag leaf thickness (FLT) in each of these trials. The one on 6H had the largest effect, with a maximum LOD 9.8 explaining up to 20.9% of phenotypic variance. FLT does not only show strong interactions with flag leaf width and flag leaf area but has also strong correlations with fertile tiller number, spike row types, kernel number per spike and heading date. Though with reduced efficiency, these loci were also detectable from assessing second last leaf of fully grown plants or even from assessing the third leaves of seedlings. Taking advantage of the high-quality genome assemblies for both parents of the mapping population used in this study, three candidate genes underlying the 6H QTL were predicted based on orthologous analysis. These results do not only broaden our understanding on genetic basis of LT and its relationship with other traits in cereal crops but also form the bases for cloning and functional analysis of genes regulating LT in barley.

BACKGROUND: The long-term health consequences of coronavirus disease 2019 (COVID-19) remain largely unclear. This study aimed to apply the Mendelian randomization (MR) design to estimate the causal associations between COVID-19 and ten cardiovascular conditions.
METHODS: Single-nucleotide polymorphisms (SNPs) associated with COVID-19 were used as instrumental variables to estimate the causal effect of COVID-19 on ten cardiovascular conditions. The random-effects inverse-variance weighted (IVW) method was conducted for the main analyses with a complementary analysis of the weighted median and MR-Egger approaches.
RESULTS: In the IVW analysis, genetically predicted COVID-19 was suggestively associated with major coronary heart disease events (OR 1.081; 95% CI 1.007-1.16; P = 0.045) and heart failure (OR 1.049; 95% CI 1.001-1.1; P = 0.045) with similar estimates in weighted median regressions. No directional pleiotropic effects were observed in both funnel plots and MR-Egger intercepts.
CONCLUSIONS: Our findings provide direct evidence that patients infected with COVID-19 are causally associated with increased risk of cardiovascular disease, especially for major coronary heart disease events and heart failure.