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.

BioKA: a curated and integrated biomarker knowledgebase for animals.

Biomarkers play an important role in various area such as personalized medicine, drug development, clinical care, and molecule breeding. However, existing animals' biomarker resources predominantly focus on human diseases, leaving a significant gap in non-human animal disease understanding and breeding research. To address this limitation, we present BioKA (Biomarker Knowledgebase for Animals, https://ngdc.cncb.ac.cn/bioka), a curated and integrated knowledgebase encompassing multiple animal species, diseases/traits, and annotated resources. Currently, BioKA houses 16 296 biomarkers associated with 951 mapped diseases/traits across 31 species from 4747 references, including 11 925 gene/protein biomarkers, 1784 miRNA biomarkers, 1043 mutation biomarkers, 773 metabolic biomarkers, 357 circRNA biomarkers and 127 lncRNA biomarkers. Furthermore, BioKA integrates various annotations such as GOs, protein structures, protein-protein interaction networks, miRNA targets and so on, and constructs an interactive knowledge network of biomarkers including circRNA-miRNA-mRNA associations, lncRNA-miRNA associations and protein-protein associations, which is convenient for efficient data exploration. Moreover, BioKA provides detailed information on 308 breeds/strains of 13 species, and homologous annotations for 8784 biomarkers across 16 species, and offers three online application tools. The comprehensive knowledge provided by BioKA not only advances human disease research but also contributes to a deeper understanding of animal diseases and supports livestock breeding.

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.

Functional Characterization of CsSWEET5a, a Cucumber Hexose Transporter That Mediates the Hexose Supply for Pollen Development and Rescues Male Fertility in Arabidopsis.

Pollen cells require large amounts of sugars from the anther to support their development, which is critical for plant sexual reproduction and crop yield. Sugars Will Eventually be Exported Transporters (SWEETs) have been shown to play an important role in the apoplasmic unloading of sugars from anther tissues into symplasmically isolated developing pollen cells and thereby affect the sugar supply for pollen development. However, among the 17 CsSWEET genes identified in the cucumber (Cucumis sativus L.) genome, the CsSWEET gene involved in this process has not been identified. Here, a member of the SWEET gene family, CsSWEET5a, was identified and characterized. The quantitative real-time PCR and ß-glucuronidase expression analysis revealed that CsSWEET5a is highly expressed in the anthers and pollen cells of male cucumber flowers from the microsporocyte stage (stage 9) to the mature pollen stage (stage 12). Its subcellular localization indicated that the CsSWEET5a protein is localized to the plasma membrane. The heterologous expression assays in yeast demonstrated that CsSWEET5a encodes a hexose transporter that can complement both glucose and fructose transport deficiencies. CsSWEET5a can significantly rescue the pollen viability and fertility of atsweet8 mutant Arabidopsis plants. The possible role of CsSWEET5a in supplying hexose to developing pollen cells via the apoplast is also discussed.

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.

Comparative Transcriptome and Metabolome Analyses of Broccoli Germplasms with Purple and Green Curds Reveal the Structural Genes and Transitional Regulators Regulating Color Formation.

Owing to the high anthocyanin content, broccoli varieties with purple curds have become more popular in food inventories, while the genetic mechanisms of anthocyanin biosynthesis pathways remain largely unknown. We bred a pair of near-isogenic lines (NILs), GB767 and PB767, whose curds exhibited green and purple colors, respectively, due to the purple sepals of florets. RNA sequencing and widely targeted metabolic analyses were conducted. Compared with GB767, eighteen anthocyanin biosynthesis-related genes exhibited significantly higher expressions in PB767, and in turn, the expression level of BolMYBL2.1 was attenuated. A comparison of the metabolites in the flavonoid biosynthetic pathways revealed 142 differentially accumulated metabolites, among which higher content of anthocyanins was responsible for the purple color of PB767. Interestingly, the total cyanidin contents were similar between the curds of NILs, whereas total delphinidin contents were increased by more than 170 times in purple curds, presumably due to a non-canonical F3'H/CYP75B gene, BolC02g015480.2J, with elevated expression in PB767. Furthermore, correlation analysis further confirmed that the identified nineteen DEGs were significantly correlated with seven differentially accumulated anthocyanins in PB767. Together, these results identified the metabolic factors and genes that contribute to the purplish curds, which could lay foundations for the breeding programs of purple broccoli.

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.

CsSWEET2, a Hexose Transporter from Cucumber (Cucumis sativus L.), Affects Sugar Metabolism and Improves Cold Tolerance in Arabidopsis.

Sugars, which are critical osmotic compounds and signalling molecules in plants, and Sugars Will Eventually be Exported Transporters (SWEETs), which constitute a novel family of sugar transporters, play central roles in plant responses to multiple abiotic stresses. In the present study, a member of the SWEET gene family from cucumber (Cucumis sativus L.), CsSWEET2, was identified and characterized. Histochemical analysis of ß-glucuronidase expression in transgenic Arabidopsis plants showed that CsSWEET2 is highly expressed in the leaves; subcellular localization indicated that CsSWEET2 proteins are localized in the plasma membrane and endoplasmic reticulum. Heterologous expression assays in yeast demonstrated that CsSWEET2 encodes an energy-independent hexose/H+ uniporter that can complement both glucose and fructose transport deficiencies. Compared with wild-type Arabidopsis plants, transgenic Arabidopsis plants overexpressing CsSWEET2 had much lower relative electrolyte leakage levels and were much more resistant to cold stress. Sugar content analysis showed that glucose and fructose levels in the transgenic Arabidopsis plants were significantly higher than those in the wild-type plants. Taken together, our results suggest that, by mediating sugar metabolism and compartmentation, CsSWEET2 plays a vital role in improving plant cold tolerance.

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.

ALKBH5 is a mammalian RNA demethylase that impacts RNA metabolism and mouse fertility.

N(6)-methyladenosine (m(6)A) is the most prevalent internal modification of messenger RNA (mRNA) in higher eukaryotes. Here we report ALKBH5 as another mammalian demethylase that oxidatively reverses m(6)A in mRNA in vitro and in vivo. This demethylation activity of ALKBH5 significantly affects mRNA export and RNA metabolism as well as the assembly of mRNA processing factors in nuclear speckles. Alkbh5-deficient male mice have increased m(6)A in mRNA and are characterized by impaired fertility resulting from apoptosis that affects meiotic metaphase-stage spermatocytes. In accordance with this defect, we have identified in mouse testes 1,551 differentially expressed genes that cover broad functional categories and include spermatogenesis-related mRNAs involved in the p53 functional interaction network. The discovery of this RNA demethylase strongly suggests that the reversible m(6)A modification has fundamental and broad functions in mammalian cells.

Characterization of Proteome Variation During Modern Maize Breeding.

The success of modern maize breeding has been demonstrated by remarkable increases in productivity with tremendous modification of agricultural phenotypes over the last century. Although the underlying genetic changes of the maize adaptation from tropical to temperate regions have been extensively studied, our knowledge is limited regarding the accordance of protein and mRNA expression levels accompanying such adaptation. Here we conducted an integrative analysis of proteomic and transcriptomic changes in a maize association panel. The minimum extent of correlation between protein and RNA levels suggests that variation in mRNA expression is often not indicative of protein expression at a population scale. This is corroborated by the observation that mRNA- and protein-based coexpression networks are relatively independent of each other, and many pQTLs arise without the presence of corresponding eQTLs. Importantly, compared with transcriptome, the subtypes categorized by the proteome show a markedly high accuracy to resemble the genomic subpopulation. These findings suggest that proteome evolved under a greater evolutionary constraint than transcriptome during maize adaptation from tropical to temperate regions. Overall, the integrated multi-omics analysis provides a functional context to interpret gene expression variation during modern maize breeding.

Aneuploid embryonic stem cells exhibit impaired differentiation and increased neoplastic potential.

Aneuploidy leads to severe developmental defects in mammals and is also a hallmark of cancer. However, whether aneuploidy is a driving cause or a consequence of tumor formation remains controversial. Paradoxically, existing studies based on aneuploid yeast and mouse fibroblasts have shown that aneuploidy is usually detrimental to cellular fitness. Here, we examined the effects of aneuploidy on mouse embryonic stem (ES) cells by generating a series of cell lines that each carries an extra copy of single chromosomes, including trisomy 6, 8, 11, 12, or 15. Most of these aneuploid cell lines had rapid proliferation rates and enhanced colony formation efficiencies. They were less dependent on growth factors for self-renewal and showed a reduced capacity to differentiate in vitro Moreover, trisomic stem cells formed teratomas more efficiently, from which undifferentiated cells can be recovered. Further investigations demonstrated that co-culture of wild-type and aneuploid ES cells or supplementation with extracellular BMP4 rescues the differentiation defects of aneuploid ES cells.

Analysis of the role of the human papillomavirus 16/18 E7 protein assay in screening for cervical intraepithelial neoplasia: a case control study.

BACKGROUND: Cervical cancer is the second-most common gynecological cancer, early screening plays a key role in the diagnosis and treatment of cervical intraepithelial neoplasia (CIN). Sustained E7 protein expression is the pathological basis for CIN and cervical cancer. METHODS: We collected the cervical cell samples of women who visited the gynecological clinic of Peking Union Medical College Hospital between September 2018 and September 2019 and submitted them to the high-risk human papillomavirus (Hr-HPV) test. We performed a magnetic particle-based chemiluminescence enzyme immunoassay to analyze the HPV16/18 E7 protein level in CIN of different severities and compared the results with those of cervical pathology (gold standard) and the HPV test. RESULTS: The positive rate of HPV16/18 E7 protein increased with the severity of CIN: 26.6% in normal tissue, 58.3% in CIN1, and 70.6% in CIN2 or higher (CIN2+). For CIN2+, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the E7 protein were 70.6, 67.9, 52.2, and 82.3%, respectively. These values of the HPV test were 86.8, 44.5, 43.7, and 87.1%, respectively. With the combination of the E7 protein assay and HPV test, the specificity for diagnosing CIN2+ was 78.1%, which was significantly higher than that of the HPV test alone. CONCLUSIONS: HPV16/18 E7 protein level is correlated with the severity of CIN and has a high concordance rate with the pathological result. For cervical cancer screening, the combination of HPV16/18 E7 protein assay and HPV test improves the CIN diagnostic specificity, detection rate, and detection accuracy.

Correction to: Analysis of the role of the human papillomavirus 16/18 E7 protein assay in screening for cervical intraepithelial neoplasia: a case control study.

An amendment to this paper has been published and can be accessed via the original article.

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.

[Database resources of the reference genome and genetic variation maps for the Chinese population].

With the implementation of the international human genome project and 1000 genome project, hundreds of Chinese individual genome sequences have been published. Establishing a high-precision Chinese population reference genome and identifying the unique genome variations are fundamental for future precision medicine research in China. To further meet the needs of scientific management and deep mining on the rapidly growing Chinese genomic data, Beijing Institute of Genomics, Chinese Academy of Sciences, has developed a Virtual Chinese Genome Database (VCGDB, http://bigd.big.ac.cn/vcg/) and Genome Variation Map (GVM, http://bigd.big.ac.cn/gvm/) based on the public whole genome sequencing data, which provides the worldwide services of data retrieval, sharing, downloading and online analysis. This paper presents the brief introduction of characteristics and functions of the two databases, as well as their future development and application prospects, aiming to provide useful information for the promotion and development of the reference genome and genome variation map database in China.