Plant genomic resources at National Genomics Data Center: assisting in data-driven breeding applications.

Genomic data serve as an invaluable resource for unraveling the intricacies of the higher plant systems, including the constituent elements within and among species. Through various efforts in genomic data archiving, integrative analysis and value-added curation, the National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), has successfully established and currently maintains a vast amount of database resources. This dedicated initiative of the NGDC facilitates a data-rich ecosystem that greatly strengthens and supports genomic research efforts. Here, we present a comprehensive overview of central repositories dedicated to archiving, presenting, and sharing plant omics data, introduce knowledgebases focused on variants or gene-based functional insights, highlight species-specific multiple omics database resources, and briefly review the online application tools. We intend that this review can be used as a guide map for plant researchers wishing to select effective data resources from the NGDC for their specific areas of study. Supplementary Information: The online version contains supplementary material available at 10.1007/s42994-023-00134-4.

OPIA: an open archive of plant images and related phenotypic traits.

High-throughput plant phenotype acquisition technologies have been extensively utilized in plant phenomics studies, leading to vast quantities of images and image-based phenotypic traits (i-traits) that are critically essential for accelerating germplasm screening, plant diseases identification and biotic & abiotic stress classification. Here, we present the Open Plant Image Archive (OPIA, https://ngdc.cncb.ac.cn/opia/), an open archive of plant images and i-traits derived from high-throughput phenotyping platforms. Currently, OPIA houses 56 datasets across 11 plants, comprising a total of 566 225 images with 2 417 186 labeled instances. Notably, it incorporates 56 i-traits of 93 rice and 105 wheat cultivars based on 18 644 individual RGB images, and these i-traits are further annotated based on the Plant Phenotype and Trait Ontology (PPTO) and cross-linked with GWAS Atlas. Additionally, each dataset in OPIA is assigned an evaluation score that takes account of image data volume, image resolution, and the number of labeled instances. More importantly, OPIA is equipped with useful tools for online image pre-processing and intelligent prediction. Collectively, OPIA provides open access to valuable datasets, pre-trained models, and phenotypic traits across diverse plants and thus bears great potential to play a crucial role in facilitating artificial intelligence-assisted breeding research.

McAN: a novel computational algorithm and platform for constructing and visualizing haplotype networks.

Haplotype networks are graphs used to represent evolutionary relationships between a set of taxa and are characterized by intuitiveness in analyzing genealogical relationships of closely related genomes. We here propose a novel algorithm termed McAN that considers mutation spectrum history (mutations in ancestry haplotype should be contained in descendant haplotype), node size (corresponding to sample count for a given node) and sampling time when constructing haplotype network. We show that McAN is two orders of magnitude faster than state-of-the-art algorithms without losing accuracy, making it suitable for analysis of a large number of sequences. Based on our algorithm, we developed an online web server and offline tool for haplotype network construction, community lineage determination, and interactive network visualization. We demonstrate that McAN is highly suitable for analyzing and visualizing massive genomic data and is helpful to enhance the understanding of genome evolution. Availability: Source code is written in C/C++ and available at https://github.com/Theory-Lun/McAN and https://ngdc.cncb.ac.cn/biocode/tools/BT007301 under the MIT license. Web server is available at https://ngdc.cncb.ac.cn/bit/hapnet/. SARS-CoV-2 dataset are available at https://ngdc.cncb.ac.cn/ncov/. Contact: songshh@big.ac.cn (Song S), zhaowm@big.ac.cn (Zhao W), baoym@big.ac.cn (Bao Y), zhangzhang@big.ac.cn (Zhang Z), ybxue@big.ac.cn (Xue Y).

Early predictive value of scoring systems and routine laboratory tests in severity and prognosis of acute pancreatitis in pregnancy.

Background: Currently, no guidelines specifically recommend scoring systems and biomarkers for early evaluation of the severity and prognosis of acute pancreatitis in pregnancy (APIP). Objectives: This study aimed to explore the early predictive value of scoring systems and routine laboratory tests on APIP severity and maternofetal prognosis. Design: This study retrospectively analyzed 62 APIP cases in a 6-year period. Methods: The predictive value of scoring systems and routine laboratory tests that were collected 24 h and 48 h after admission, for APIP severity and fetal loss, were analyzed. Results: To detect severe acute pancreatitis (SAP), a 24-h Bedside Index for severity in acute pancreatitis (BISAP) achieved a higher area under the curve (AUC) value of 0.910 than the Acute Physiology and Chronic Health Evaluation II (AUC = 0.898) and Ranson score (AUC = 0.880). The combination of BISAP, glucose, neutrophil-to-lymphocyte ratio (NLR), hematocrit (Hct), and serum creatinine (Scr) provided an AUC value of 0.984, which had greater predictive power than BISAP (p = 0.015). 24-h BISAP and Hct were independent risk factors for predicting SAP of APIP. The cutoff values of Hct and blood urea nitrogen (BUN) to predict SAP were 35.60% and 3.75 mmol/l in the APIP. Furthermore, 24-h BISAP had the highest predictive power (AUC = 0.958) for fetal loss. Conclusion: BISAP is a convenient and reliable indicator for the early prediction of SAP and fetal loss in APIP. The combination of BISAP, glucose, NLR, Hct and Scr proved to be the optimal early markers for the prediction of SAP in APIP within 24 h after admission. In addition, Hct > 35.60% and BUN > 3.75 mmol/l may be suitable thresholds for predicting SAP in APIP.

A New Method for Training CycleGAN to Enhance Images of Cold Seeps in the Qiongdongnan Sea.

Clear underwater images can help researchers detect cold seeps, gas hydrates, and biological resources. However, the quality of these images suffers from nonuniform lighting, a limited range of visibility, and unwanted signals. CycleGAN has been broadly studied in regard to underwater image enhancement, but it is difficult to apply the model for the further detection of Haima cold seeps in the South China Sea because the model can be difficult to train if the dataset used is not appropriate. In this article, we devise a new method of building a dataset using MSRCR and choose the best images based on the widely used UIQM scheme to build the dataset. The experimental results show that a good CycleGAN could be trained with the dataset using the proposed method. The model has good potential for applications in detecting the Haima cold seeps and can be applied to other cold seeps, such as the cold seeps in the North Sea. We conclude that the method used for building the dataset can be applied to train CycleGAN when enhancing images from cold seeps.

Ribavirin extends the lifespan of Caenorhabditis elegans through AMPK-TOR Signaling.

Aging is a process accompanied by widespread degenerative changes which are a major cause of human disease and disability. One goal of aging research is to develop interventions or drugs that can extend organism lifespan and treat age-related diseases. Here, we report the identification of a broad spectrum anti-viral agent, ribavirin, as a potential pharmacological aging intervention. Ribavirin extended the lifespan and healthspan of Caenorhabditis elegans by inhibiting Target of Rapamycin (TOR) signaling and activating AMP-activated protein kinase (AMPK). Moreover, our data indicate that ribavirin activated AMPK by reducing the levels of adenosine triphosphate (ATP) and lysosomal v-ATPase-Ragulator-AXIN Complex. Thus, our studies successfully identify ribavirin as a potential anti-aging drug, and indicate that its anti-aging effect is mediated via AMPK-TOR signaling.

HGD: an integrated homologous gene database across multiple species.

Homology is fundamental to infer genes' evolutionary processes and relationships with shared ancestry. Existing homolog gene resources vary in terms of inferring methods, homologous relationship and identifiers, posing inevitable difficulties for choosing and mapping homology results from one to another. Here, we present HGD (Homologous Gene Database, https://ngdc.cncb.ac.cn/hgd), a comprehensive homologs resource integrating multi-species, multi-resources and multi-omics, as a complement to existing resources providing public and one-stop data service. Currently, HGD houses a total of 112 383 644 homologous pairs for 37 species, including 19 animals, 16 plants and 2 microorganisms. Meanwhile, HGD integrates various annotations from public resources, including 16 909 homologs with traits, 276 670 homologs with variants, 398 573 homologs with expression and 536 852 homologs with gene ontology (GO) annotations. HGD provides a wide range of omics gene function annotations to help users gain a deeper understanding of gene function.

GWAS Atlas: an updated knowledgebase integrating more curated associations in plants and animals.

GWAS Atlas (https://ngdc.cncb.ac.cn/gwas/) is a manually curated resource of genome-wide genotype-to-phenotype associations for a wide range of species. Here, we present an updated implementation of GWAS Atlas by curating and incorporating more high-quality associations, with significant improvements and advances over the previous version. Specifically, the current release of GWAS Atlas incorporates a total of 278,109 curated genotype-to-phenotype associations for 1,444 different traits across 15 species (10 plants and 5 animals) from 830 publications and 3,432 studies. A collection of 6,084 lead SNPs of 439 traits and 486 experiment-validated causal variants of 157 traits are newly added. Moreover, 1,056 trait ontology terms are newly defined, resulting in 1,172 and 431 terms for Plant Phenotype and Trait Ontology and Animal Phenotype and Trait Ontology, respectively. Additionally, it is equipped with four online analysis tools and a submission platform, allowing users to perform data analysis and data submission. Collectively, as a core resource in the National Genomics Data Center, GWAS Atlas provides valuable genotype-to-phenotype associations for a diversity of species and thus plays an important role in agronomic trait study and molecular breeding.

Accurate identification of taxon-specific molecular markers in plants based on DNA signature sequence.

Accurate identification of plants remains a significant challenge for taxonomists and is the basis for plant diversity conservation. Although DNA barcoding methods are commonly used for plant identification, these are limited by the low amplification success and low discriminative power of selected genomic regions. In this study, we developed a k-mer-based approach, the DNA signature sequence (DSS), to accurately identify plant taxon-specific markers, especially at the species level. DSS is a constant-length nucleotide sequence capable of identifying a taxon and distinguishing it from other taxa. In this study, we performed the first large-scale study of DSS markers in plants. DSS candidates of 3899 angiosperm plant species were calculated based on a chloroplast data set with 4356 assemblies. Using Sanger sequencing of PCR amplicons and high-throughput sequencing, DSSs were validated in four and 165 species, respectively. Based on this, the universality of the DSSs was over 79.38%. Several indicators influencing DSS marker identification and detection have also been evaluated, and common criteria for DSS application in plant identification have been proposed.

Polymelamine Formaldehyde-Coated MIL-101 as an Efficient Dual-Functional Core-Shell Composite to Catalyze the Deacetalization-Knoevenagel Tandem Reaction.

Porous organic polymer (POP) coated on a metal-organic framework (MOF) has the functions and advantages of MOF and POP at the same time and has excellent catalytic ability. In this study, an efficient dual-functional core-shell composite MOF@POP with Lewis acid and Brønsted base sites was synthesized using the impregnation method in which MIL-101(Cr) was the core component and polymelamine formaldehyde (PMF) was the shell component. Most importantly, the obtained MIL-101(Cr)@PMF showed perfect catalytic activity in the deacetalization-Knoevenagel tandem reaction. In addition, it could still maintain ultrahigh physical and chemical stability.

Dietary Supplement of Anoectochilus roxburghii (Wall.) Lindl. Polysaccharides Ameliorates Cognitive Dysfunction Induced by High Fat Diet via "Gut-Brain" Axis.

Purpose: Anoectochilus roxburghii (Wall.) Lindl. polysaccharides (ARPs) have been reported to exhibit multiple pharmacological activities including anti-inflammatory and anti-hyperglycemia. This study aims to investigate the effect of ARPs on cognitive dysfunction induced by high fat diet (HFD). Methods: Six-week-old male mice were treated with ARPs by dietary supplementation for 14 weeks. The effect of ARPs on cognitive function was determined by assessing the changes in spatial learning and memory ability, neurotrophic factors in hippocampus, inflammatory parameters, intestinal barrier integrity, and gut microbiota. Results: ARPs supplementation can effectively ameliorate cognitive dysfunction, decrease the phosphorylation levels of Tau protein in hippocampus. Meanwhile, the increased body weight, plasma glucose, total cholesterol, inflammatory factors induced by HFD were abolished by ARPs treatment. Furthermore, ARPs treatment restored the intestinal epithelial barrier as evidenced by upregulation of intestinal tight junction proteins. Additionally, ARPs supplementation significantly decreased the relative abundance of several bacteria genus such as Parabacteroides, which may play regulatory roles in cognitive function. Conclusion: These results suggest that ARPs might be a promising strategy for the treatment of cognitive dysfunction induced by HFD. Mechanistically, alleviation of cognitive dysfunction by ARPs might be associated with the "gut-brain" axis.

Therapeutic effect and mechanism of polysaccharides from Anoectochilus Roxburghii (Wall.) Lindl. in diet-induced obesity.

BACKGROUND: Recent studies have shown that polysaccharides from Anoectochilus roxburghii (Wall.) Lindl. (ARPs) can reduce blood glucose levels, ameliorate oxidative stress and inflammation. However, whether ARPs have a beneficial effect on diet-induced obesity remain to be determined. PURPOSE: This study aims to investigate the effect and mechanism of ARPs in improving obesity and metabolic disorders induced by high-fat diet (HFD). METHODS: In this study, 6-week-old male mice were fed with HFD or chow diet for 13 weeks, and a dietary supplementation with ARPs was carried out. Glucose tolerance test and insulin tolerance test were performed to measure the glucose tolerance and insulin sensitivity. Adipose tissue and liver were isolated for analysis by qRT-PCR, Western blotting, hematoxylin-eosin staining and immunostaining. RESULTS: At week 13, body weight and fat mass were significantly increased by HFD, but ARPs supplementation abolished these phenotypes. Compared with HFD group, thermogenic genes including Ucp-1, Pgc-1α, Prdm16 and Dio2 in adipose tissue were up-regulated in ARPs-treated mice. In addition, ARPs decreased liver lipid accumulation by reducing lipid synthesis and increasing oxidation. Meanwhile, dyslipidemia and insulin resistance induced by HFD were improved by ARPs. Mechanistically, ARPs can promote fat thermogenesis via AMPK/SIRT1/PGC-1α signaling pathway. CONCLUSION: Dietary supplementation of ARPs can protect mice against diet-induced obesity, fatty liver and insulin resistance. Our study reveals a potential therapeutic effect for ARPs in regulating energy homeostasis.

The Effect of Health Education Combined with Personalized Psychological Nursing Intervention on Pregnancy Outcome of Pregnant Women with Gestational Diabetes Mellitus.

Objective: To study the effect of health education combined with personalized psychological nursing intervention on pregnancy outcome of pregnant women with gestational diabetes mellitus (GDM). Methods: 170 patients with GDM admitted to Guangdong Women and Children Hospital from January 2018 to December 2018 were selected as study subjects and randomly divided into two groups. During the period from diagnosis of GDM to termination of pregnancy, both groups were given routine education and routine examination, and the intervention group adopted health education combined with personalized psychological nursing interventions during pregnancy. The pregnancy weight, blood glucose index, compliance, disease awareness, self-adjustment management ability, satisfaction, and pregnancy outcome were measured before and after the intervention. Results: There were no statistically significant differences in pregnancy weight, fasting plasma glucose, and 2 h postprandial blood glucose between the two groups before intervention (P = 0.768, 0.605, and 0.762). After intervention, lower levels of the above indicators were obtained in the intervention group than in the control group (P < 0.001). The compliance and satisfaction with the intervention in the intervention group were significantly higher than those in the control group (P < 0.001). The intervention group had remarkably higher disease awareness rate and self-psychological adjustment and management ability than the control group (P < 0.001). Better pregnancy outcomes were observed in the intervention group compared with the control group (P < 0.001). Conclusion: For patients with GDM, health education combined with personalized psychological nursing on the basis of the conventional nursing can effectively control patients' condition and ensure a better pregnancy outcome, which merits widespread promotion.

Single Cell Proteomics Profiling Reveals That Embryo-Secreted TNF-α Plays a Critical Role During Embryo Implantation to the Endometrium.

It has been long-known that endometrium-secreted cytokines play a critical role during embryo implantation. However, whether cytokines secreted from the embryo are relevant to the process of embryo implantation remains unclear. The concentration of cytokines in embryo culture medium was tested using a newly developed, high-sensitivity single-cell proteomic platform and evaluated in comparison to embryo quality and clinical outcome. The effect of TNF-α on embryo and endometrium Ishikawa cells was investigated using immunofluorescence staining, CCK-8 assay, TUNEL staining, and RT-qPCR. Of the 10 cytokines measured, only TNF-α concentration was significantly higher in the group with embryo implantation failure. Immunofluorescence staining showed that the expression of TNF-α was unevenly distributed in blastocysts, and the expression level was significantly correlated with the blastocyst inner cell mass (ICM) quality score. Gene profiling showed that addition of TNF-α led to increased expression of tumor necrosis factor receptor 1 (TNFR1) and apoptosis-related genes and that this could be inhibited by the TNF-α receptor inhibitor etanercept (ETA). In addition, an increased expression of water and ion channels, including AQP3, CFTR, ENaCA, and CRISP2 was also observed which could also be inhibited by ETA. Our results show that higher embryo-secreted TNF-α levels are associated with implantation failure through activation of TNF-α receptor, and TNF-α may be an independent predictor for pre-transfer assessment of the embryo development potential in IVF patients.

Evaluation of EpCAM-specific exosomal lncRNAs as potential diagnostic biomarkers for lung cancer using droplet digital PCR.

Accumulating evidence demonstrated that long non-coding RNAs (lncRNAs) derived from exosomes had the potential to be diagnostic markers for lung cancer. However, the diagnostic value of lncRNAs from epithelial cell adhesion molecule (EpCAM)-positive exosomes remains unclear. In the study, serum EpCAM-positive exosomes were isolated with magnetic beads, and their role in lung cancer was investigated in vitro and in vivo. The copy numbers of lncRNAs RP11-77G23.5 and PHEX-AS1 in EpCAM-specific exosomes were quantified by droplet digital PCR (ddPCR). The diagnostic value of RP11-77G23.5 and PHEX-AS1 was tested in the training cohort and verified in the validation cohort. We found that EpCAM-specific exosomes could promote lung cancer development in vitro and in vivo. RP11-77G23.5 and PHEX-AS1 were significantly elevated in EpCAM-specific exosomes from lung cancer patients and could distinguish malignant from benign lung tumors. The amounts of RP11-77G23.5 were statistically higher in the subtype of lung adenocarcinoma (LUAC) than that of lung squamous cell carcinoma (LUSC), showing its capability to subtype LUAC and LUSC, while PHEX-AS1 exhibited distinct expression signatures between lower and higher tumor stages, and without and with distant metastasis, indicating its association with lung cancer progression. In conclusion, the EpCAM-specific exosomal lncRNAs RP11-77G23.5 and PHEX-AS1 may be promising diagnostic biomarkers for lung cancer. KEY MESSAGES: Serum EpCAM-positive exosomes promote lung cancer development in vitro and in vivo. Two EpCAM-specific exosomal lncRNAs can be simultaneously detected by RT-ddPCR. EpCAM-specific exosomal RP11-77G23.5 has the potential to subtype LUAC and LUSC. EpCAM-specific exosomal PHEX-AS1 is associated with lung cancer progression.

Genomic Epidemiology of SARS-CoV-2 in Pakistan.

COVID-19 has swept globally and Pakistan is no exception. To investigate the initial introductions and transmissions of the SARS-CoV-2 in Pakistan, we performed the largest genomic epidemiology study of COVID-19 in Pakistan and generated 150 complete SARS-CoV-2 genome sequences from samples collected from March 16 to June 1, 2020. We identified a total of 347 mutated positions, 31 of which were over-represented in Pakistan. Meanwhile, we found over 1000 intra-host single-nucleotide variants (iSNVs). Several of them occurred concurrently, indicating possible interactions among them or coevolution. Some of the high-frequency iSNVs in Pakistan were not observed in the global population, suggesting strong purifying selections. The genomic epidemiology revealed five distinctive spreading clusters. The largest cluster consisted of 74 viruses which were derived from different geographic locations of Pakistan and formed a deep hierarchical structure, indicating an extensive and persistent nation-wide transmission of the virus that was probably attributed to a signature mutation (G8371T in ORF1ab) of this cluster. Furthermore, 28 putative international introductions were identified, several of which are consistent with the epidemiological investigations. In all, this study has inferred the possible pathways of introductions and transmissions of SARS-CoV-2 in Pakistan, which could aid ongoing and future viral surveillance and COVID-19 control.