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).

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.

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.

Genome Variation Map: a worldwide collection of genome variations across multiple species.

The Genome Variation Map (GVM; http://bigd.big.ac.cn/gvm/) is a public data repository of genome variations. It aims to collect and integrate genome variations for a wide range of species, accepts submissions of different variation types from all over the world and provides free open access to all publicly available data in support of worldwide research activities. Compared with the previous version, particularly, a total of 22 species, 115 projects, 55 935 samples, 463 429 609 variants, 66 220 associations and 56 submissions (as of 7 September 2020) were newly added in the current version of GVM. In the current release, GVM houses a total of ∼960 million variants from 41 species, including 13 animals, 25 plants and 3 viruses. Moreover, it incorporates 64 819 individual genotypes and 260 393 manually curated high-quality genotype-to-phenotype associations. Since its inception, GVM has archived genomic variation data of 43 754 samples submitted by worldwide users and served >1 million data download requests. Collectively, as a core resource in the National Genomics Data Center, GVM provides valuable genome variations for a diversity of species and thus plays an important role in both functional genomics studies and molecular breeding.

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.

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.

GWAS Atlas: a curated resource of genome-wide variant-trait associations in plants and animals.

GWAS Atlas (https://bigd.big.ac.cn/gwas/) is a manually curated resource of genome-wide variant-trait associations for a wide range of species. Unlike existing related resources, it features comprehensive integration of a high-quality collection of 75 467 variant-trait associations for 614 traits across 7 cultivated plants (cotton, Japanese apricot, maize, rapeseed, rice, sorghum and soybean) and two domesticated animals (goat and pig), which were manually curated from 254 publications. We integrated these associations into GWAS Atlas and presented them in terms of variants, genes, traits, studies and publications. More importantly, all associations and traits were annotated and organized based on a suite of ontologies (Plant Trait Ontology, Animal Trait Ontology for Livestock, etc.). Taken together, GWAS Atlas integrates high-quality curated GWAS associations for animals and plants and provides user-friendly web interfaces for data browsing and downloading, accordingly serving as a valuable resource for genetic research of important traits and breeding application.

Expression characteristics of pineal miRNAs at ovine different reproductive stages and the identification of miRNAs targeting the AANAT gene.

BACKGROUND: Many recent studies have shown that miRNAs play important roles in the regulation of animal reproduction, including seasonal reproduction. The pineal gland is a crucial hub in the regulation of seasonal reproduction. However, little is known about the expression characteristics of pineal miRNAs in different reproductive seasons (anestrus and breeding season). Therefore, the expression profiles and regulatory roles of ovine pineal miRNAs were investigated during different reproductive stages using Solexa sequencing technology and dual luciferase reporter assays. RESULTS: A total of 427 miRNAs were identified in the sheep pineal gland. Significant differences in miRNA expression were demonstrated between anestrus and the breeding season in terms of the frequency distributions of miRNA lengths, number of expressed miRNAs, and specifically and highly expressed miRNAs in each reproductive stage. KEGG analysis of the differentially expressed (DE) miRNAs between anestrus and the breeding season indicated that they are significantly enriched in pathways related to protein synthesis, secretion and uptake. Furthermore, transcriptome analysis revealed that many target genes of DE miRNAs in the ribosome pathway showed relatively low expression in the breeding season. On the other hand, analyses combining miRNA-gene expression data with target relationship validation in vitro implied that miR-89 may participate in the negative regulation of aralkylamine N-acetyltransferase (AANAT) mRNA expression by targeting its 3'UTR at a unique binding site. CONCLUSIONS: Our results provide new insights into the expression characteristics of sheep pineal miRNAs at different reproductive stages and into the negative regulatory effects of pineal miRNAs on AANAT mRNA expression.

Genome Variation Map: a data repository of genome variations in BIG Data Center.

The Genome Variation Map (GVM; http://bigd.big.ac.cn/gvm/) is a public data repository of genome variations. As a core resource in the BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, GVM dedicates to collect, integrate and visualize genome variations for a wide range of species, accepts submissions of different types of genome variations from all over the world and provides free open access to all publicly available data in support of worldwide research activities. Unlike existing related databases, GVM features integration of a large number of genome variations for a broad diversity of species including human, cultivated plants and domesticated animals. Specifically, the current implementation of GVM not only houses a total of ∼4.9 billion variants for 19 species including chicken, dog, goat, human, poplar, rice and tomato, but also incorporates 8669 individual genotypes and 13 262 manually curated high-quality genotype-to-phenotype associations for non-human species. In addition, GVM provides friendly intuitive web interfaces for data submission, browse, search and visualization. Collectively, GVM serves as an important resource for archiving genomic variation data, helpful for better understanding population genetic diversity and deciphering complex mechanisms associated with different phenotypes.

The 2019 novel coronavirus resource.

An ongoing outbreak of a novel coronavirus infection in Wuhan, China since December 2019 has led to 31,516 infected persons and 638 deaths across 25 countries (till 16:00 on February 7, 2020). The virus causing this pneumonia was then named as the 2019 novel coronavirus (2019-nCoV) by the World Health Organization. To promote the data sharing and make all relevant information of 2019-nCoV publicly available, we construct the 2019 Novel Coronavirus Resource (2019nCoVR, https://bigd.big.ac.cn/ncov). 2019nCoVR features comprehensive integration of genomic and proteomic sequences as well as their metadata information from the Global Initiative on Sharing All Influenza Data, National Center for Biotechnology Information, China National GeneBank, National Microbiology Data Center and China National Center for Bioinformation (CNCB)/National Genomics Data Center (NGDC). It also incorporates a wide range of relevant information including scientific literatures, news, and popular articles for science dissemination, and provides visualization functionalities for genome variation analysis results based on all collected 2019-nCoV strains. Moreover, by linking seamlessly with related databases in CNCB/NGDC, 2019nCoVR offers virus data submission and sharing services for raw sequence reads and assembled sequences. In this report, we provide comprehensive descriptions on data deposition, management, release and utility in 2019nCoVR, laying important foundations in aid of studies on virus classification and origin, genome variation and evolution, fast detection, drug development and pneumonia precision prevention and therapy.

Integrated analysis of phenome, genome, and transcriptome of hybrid rice uncovered multiple heterosis-related loci for yield increase.

Hybrid rice is the dominant form of rice planted in China, and its use has extended worldwide since the 1970s. It offers great yield advantages and has contributed greatly to the world's food security. However, the molecular mechanisms underlying heterosis have remained a mystery. In this study we integrated genetics and omics analyses to determine the candidate genes for yield heterosis in a model two-line rice hybrid system, Liang-you-pei 9 (LYP9) and its parents. Phenomics study revealed that the better parent heterosis (BPH) of yield in hybrid is not ascribed to BPH of all the yield components but is specific to the BPH of spikelet number per panicle (SPP) and paternal parent heterosis (PPH) of effective panicle number (EPN). Genetic analyses then identified multiple quantitative trait loci (QTLs) for these two components. Moreover, a number of differentially expressed genes and alleles in the hybrid were mapped by transcriptome profiling to the QTL regions as possible candidate genes. In parallel, a major QTL for yield heterosis, rice heterosis 8 (RH8), was found to be the DTH8/Ghd8/LHD1 gene. Based on the shared allelic heterozygosity of RH8 in many hybrid rice cultivars, a common mechanism for yield heterosis in the present commercial hybrid rice is proposed.

Delayed diagnosis of spontaneous bladder rupture: a rare case report.

BACKGROUND: Bladder rupture caused by trauma or pelvic fracture is very common, and can be easily diagnosed. However, Spontaneous rupture of the bladder is rare. Reported by Peters PC. (Peters, Urol Clin N Am 16:279-82, 1989): The incidence of spontaneous bladder rupture is 1: 126000. During childbirth, the occurrence rate of this disease is lower than that of the former. It is very difficult to make an early diagnosis of the spontaneous rupture of the bladder during childbirth, which eventually results in high maternal mortality. Due to peritoneal reabsorption, the patient may show high levels of serum creatinine and potassium, and this would easily be misdiagnosed as acute renal failure. However, these patients have normal renal function, hence the diagnosis of renal failure is incorrect. CASE PRESENTATION: A 23 year-old female patient had her first pregnancy and delivered a full-term healthy baby girl. After delivery, the patient developed fever, oliguria, massive ascites, high serum creatinine and high serum potassium. The patient was initially diagnosed with acute renal failure, however treatment for her condition was ineffective. After further examination, the patient was diagnosed with intraperitoneal bladder rupture. The patient was treated for bladder rupture, made a full recovery and was discharged. CONCLUSIONS: Sudden onset of massive ascites and renal failure due to abnormal serum biochemical characteristics after delivery should be first diagnosed as spontaneous bladder rupture. However, bladder radiography may suggest a false negative result, hence cystoscopy should be performed to confirm the diagnosis. The ratio between ascites creatinine and serum creatinine would be helpful for early diagnosis and to determine the time of rupture. Conservative management or surgical repair should be used to treat bladder rupture.

Characterization and comparative profiling of ovarian microRNAs during ovine anestrus and the breeding season.

BACKGROUND: Seasonal estrus is a critical limiting factor of animal fecundity, and it involves changes in both ovarian biology and hormone secretion in different seasons. Previous studies indicate that two classes of small RNAs (miRNAs and piRNAs) play important regulatory roles in ovarian biology. To understand the roles of small RNA-mediated post-transcriptional regulation in ovine seasonal estrus, the variation in expression patterns of ovarian small RNAs during anestrus and the breeding season were analyzed using Solexa sequencing technology. In addition, reproductive hormone levels were determined during ovine anestrus and the breeding season. RESULTS: A total of 483 miRNAs (including 97 known, 369 conserved and 17 predicated novel miRNAs), which belong to 183 different miRNA families, were identified in ovaries of Tan sheep and Small Tail Han (STH) sheep. Compared with the three stages of the breeding season, 25 shared significantly differentially expressed (including 19 up- and six down-regulated) miRNAs were identified in ovine anestrus. KEGG Pathway analysis revealed that the target genes for some of the differentially expressed miRNAs were involved in reproductive hormone related pathways (e.g. steroid biosynthesis, androgen and estrogen metabolism and GnRH signaling pathway) as well as follicular/luteal development related pathways. Moreover, the expression of the differentially expressed miRNAs and most of their target genes were negatively correlated in the above pathways. Furthermore, the levels of estrogen, progesterone and LH in ovine anestrus were significantly lower than those in the breeding season. Combining the results of pathway enrichment analysis, expression of target genes and hormone measurement, we suggest that these differentially expressed miRNAs in anestrus might participate in attenuation of ovarian activity by regulating the above pathways. Besides miRNAs, a large and unexpectedly diverse set of piRNAs were also identified. CONCLUSIONS: The miRNA profiles of ovine ovaries in anestrus were presented for the first time. The identification and characterization of miRNAs that are differentially expressed between ovine anestrus and the breeding season will help understanding of the role of miRNAs in the regulation of seasonal estrus, and provides candidates for determining miRNAs which could be potentially used to regulate ovine seasonal estrus.

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.

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.

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.

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.

wapRNA: a web-based application for the processing of RNA sequences.

SUMMARY: mRNA/miRNA-seq technology is becoming the leading technology to globally profile gene expression and elucidate the transcriptional regulation mechanisms in living cells. Although there are many tools available for analyzing RNA-seq data, few of them are available as easy accessible online web tools for processing both mRNA and miRNA data for the RNA-seq based user community. As such, we have developed a comprehensive web application tool for processing mRNA-seq and miRNA-seq data. Our web tool wapRNA includes four different modules: mRNA-seq and miRNA-seq sequenced from SOLiD or Solexa platform and all the modules were tested on previously published experimental data. We accept raw sequence data with an optional reads filter, followed by mapping and gene annotation or miRNA prediction. wapRNA also integrates downstream functional analyses such as Gene Ontology, KEGG pathway, miRNA targets prediction and comparison of gene's or miRNA's different expression in different samples. Moreover, we provide the executable packages for installation on user's local server. AVAILABILITY: wapRNA is freely available for use at http://waprna.big.ac.cn. The executable packages and the instruction for installation can be downloaded from our web site. CONTACT: husn@big.ac.cn; songshh@big.ac.cn. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.