TCOD: an integrated resource for tropical crops.

Tropical crops are vital for tropical agriculture, with resource scarcity, functional diversity and extensive market demand, providing considerable economic benefits for the world's tropical agriculture-producing countries. The rapid development of sequencing technology has promoted a milestone in tropical crop research, resulting in the generation of massive amount of data, which urgently needs an effective platform for data integration and sharing. However, the existing databases cannot fully satisfy researchers' requirements due to the relatively limited integration level and untimely update. Here, we present the Tropical Crop Omics Database (TCOD, https://ngdc.cncb.ac.cn/tcod), a comprehensive multi-omics data platform for tropical crops. TCOD integrates diverse omics data from 15 species, encompassing 34 chromosome-level de novo assemblies, 1 255 004 genes with functional annotations, 282 436 992 unique variants from 2048 WGS samples, 88 transcriptomic profiles from 1997 RNA-Seq samples and 13 381 germplasm items. Additionally, TCOD not only employs genes as a bridge to interconnect multi-omics data, enabling cross-species comparisons based on homology relationships, but also offers user-friendly online tools for efficient data mining and visualization. In short, TCOD integrates multi-species, multi-omics data and online tools, which will facilitate the research on genomic selective breeding and trait biology of tropical crops.

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.

TSomVar: a tumor-only somatic and germline variant identification method with random forest.

Somatic variants act as critical players during cancer occurrence and development. Thus, an accurate and robust method to identify them is the foundation of cutting-edge cancer genome research. However, due to low accessibility and high individual-/sample-specificity of the somatic variants in tumor samples, the detection is, to date, still crammed with challenges, particularly when lacking paired normal samples as control. To solve this burning issue, we developed a tumor-only somatic and germline variant identification method (TSomVar) using the random forest algorithm established on sample-specific variant datasets derived from genotype imputation, reads-mapping level annotation and functional annotation. We trained TSomVar by using genomic variant datasets of three major cancer types: colorectal cancer, hepatocellular carcinoma and skin cutaneous melanoma. Compared with existing tumor-only somatic variant identification tools, TSomVar shows excellent performances in somatic variant detection with higher accuracy and better capability of recalling for test datasets from colorectal cancer and skin cutaneous melanoma. In addition, TSomVar is equipped with the competence of accurately identifying germline variants in tumor samples. Taken together, TSomVar will undoubtedly facilitate and revolutionize somatic variant explorations in cancer research.

CancerSCEM: a database of single-cell expression map across various human cancers.

With the proliferating studies of human cancers by single-cell RNA sequencing technique (scRNA-seq), cellular heterogeneity, immune landscape and pathogenesis within diverse cancers have been uncovered successively. The exponential explosion of massive cancer scRNA-seq datasets in the past decade are calling for a burning demand to be integrated and processed for essential investigations in tumor microenvironment of various cancer types. To fill this gap, we developed a database of Cancer Single-cell Expression Map (CancerSCEM, https://ngdc.cncb.ac.cn/cancerscem), particularly focusing on a variety of human cancers. To date, CancerSCE version 1.0 consists of 208 cancer samples across 28 studies and 20 human cancer types. A series of uniformly and multiscale analyses for each sample were performed, including accurate cell type annotation, functional gene expressions, cell interaction network, survival analysis and etc. Plus, we visualized CancerSCEM as a user-friendly web interface for users to browse, search, online analyze and download all the metadata as well as analytical results. More importantly and unprecedentedly, the newly-constructed comprehensive online analyzing platform in CancerSCEM integrates seven analyze functions, where investigators can interactively perform cancer scRNA-seq analyses. In all, CancerSCEM paves an informative and practical way to facilitate human cancer studies, and also provides insights into clinical therapy assessments.

Fabrication of Azacrown Ether-Embedded Covalent Organic Frameworks for Enhanced Cathode Performance in Aqueous Ni-Zn Batteries.

Crown ethers (CEs), known for their exceptional host-guest complexation, offer potential as linkers in covalent organic frameworks (COFs) for enhanced performance in catalysis and host-guest binding. However, their highly flexible conformation and low symmetry limit the diversity of CE-derived COFs. Here, we introduce a novel C3-symmetrical azacrown ether (ACE) building block, tris(pyrido)[18]crown-6 (TPy18C6), for COF fabrication (ACE-COF-1 and ACE-COF-2) via reticular synthesis. This approach enables precise integration of CEs into COFs, enhancing Ni2+ ion immobilization while maintaining crystallinity. The resulting Ni2+-doped COFs (Ni@ACE-COF-1 and Ni@ACE-COF-2) exhibit high discharge capacity (up to 1.27 mAh·cm-2 at 8 mA·cm-2) and exceptional cycling stability (>1000 cycles) as cathode materials in aqueous alkaline nickel-zinc batteries. This study serves as an exemplar of the seamless integration of macrocyclic chemistry and reticular chemistry, laying the groundwork for extending the macrocyclic-synthon driven strategy to a diverse array of COF building blocks, ultimately yielding advanced materials tailored for specific applications.

RefRGim: an intelligent reference panel reconstruction method for genotype imputation with convolutional neural networks.

Genotype imputation is a statistical method for estimating missing genotypes from a denser haplotype reference panel. Existing methods usually performed well on common variants, but they may not be ideal for low-frequency and rare variants. Previous studies showed that the population similarity between study and reference panels is one of the key factors influencing the imputation accuracy. Here, we developed an imputation reference panel reconstruction method (RefRGim) using convolutional neural networks (CNNs), which can generate a study-specified reference panel for each input data based on the genetic similarity of individuals from current study and references. The CNNs were pretrained with single nucleotide polymorphism data from the 1000 Genomes Project. Our evaluations showed that genotype imputation with RefRGim can achieve higher accuracies than original reference panel, especially for low-frequency and rare variants. RefRGim will serve as an efficient reference panel reconstruction method for genotype imputation. RefRGim is freely available via GitHub: https://github.com/shishuo16/RefRGim.

RETRACTED: CGVD: a genomic variation database for Chinese populations.

Precision medicine calls upon deeper coverage of population-based sequencing and thorough gene-content and phenotype-based analysis, which lead to a population-associated genomic variation map or database. The Chinese Genomic Variation Database (CGVD; https://bigd.big.ac.cn/cgvd/) is such a database that has combined 48.30 million (M) SNVs and 5.77 M small indels, identified from 991 Chinese individuals of the Chinese Academy of Sciences Precision Medicine Initiative Project (CASPMI) and 301 Chinese individuals of the 1000 Genomes Project (1KGP). The CASPMI project includes whole-genome sequencing data (WGS, 25-30×) from ∼1000 healthy individuals of the CASPMI cohort. To facilitate the usage of such variations for pharmacogenomics studies, star-allele frequencies of the drug-related genes in the CASPMI and 1KGP populations are calculated and provided in CGVD. As one of the important database resources in BIG Data Center, CGVD will continue to collect more genomic variations and to curate structural and functional annotations to support population-based healthcare projects and studies in China and worldwide.

Exome sequencing identifies new somatic alterations and mutation patterns of tongue squamous cell carcinoma in a Chinese population.

Tongue squamous cell carcinoma (TSCC) is an aggressive group of tumors characterized by high rates of regional lymph node metastasis and local recurrence. Emerging evidence has revealed genetic variations of TSCC across different geographical regions due to the impact of multiple risk factors such as chewing betel-quid. However, we know little of the mutational processes of TSCC in the Chinese population without the history of chewing betel-quid/tobacco. To explore the mutational spectrum of this disease, we performed whole-exome sequencing of sample pairs, comprising tumors and normal tissue, from 82 TSCC patients. In addition to identifying seven previously known TSCC-associated genes (TP53, CDKN2A, PIK3CA, NOTCH1, ASXL1, USH2A, and CSMD3), the analysis revealed six new genes (GNAQ, PRG4, RP1, ZNF16, NBEA, and PTPRC) that had not been reported previously in TSCC. Our in vitro experiments identified ZNF16 for the first time as a solid tumor associated gene to promote malignancy of TSCC cells. We also identified a microRNA (miR-585-5p) encoded by the 5q35.1 region and characterized it as a tumor suppressor by targeting SOX9. At least one non-silent mutation of genes involved in the 10 canonical oncogenic pathways (Notch, RTK-RAS, PI3K, Wnt, Cell cycle, p53, Myc, Hippo, TGFß, and Nrf2) was found in 82.9% of cases. Collectively, our data extend the spectrum of TSCC mutations and define novel diagnosis markers and potential clinical targets for TSCC. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

GSA-Human: Genome Sequence Archive for Human.

The Genome Sequence Archive for Human (GSA-Human) is a data repository specialized for human genetic related data derived from biomedical researches, and also supports the data collection and management of National Key Research and Development Projects. GSA-Human has a data security management strategy according to the national regulations of human genetic resources. It provides two different models of data access: Open-access and Controlled-access. Open-access data are universally and freely accessible for global researchers, while Controlled-access ensures that data are accessed only by authorized users with the permission of the Data Access Committee (DAC). Till July 2021, GSA-Human has housed more than 5.27 PB of data from 750 datasets.

Correction: Comprehensively benchmarking applications for detecting copy number variation.

[This corrects the article DOI: 10.1371/journal.pcbi.1007069.].

Comprehensively benchmarking applications for detecting copy number variation.

MOTIVATION: Recently, copy number variation (CNV) has gained considerable interest as a type of genomic variation that plays an important role in complex phenotypes and disease susceptibility. Since a number of CNV detection methods have recently been developed, it is necessary to help investigators choose suitable methods for CNV detection depending on their objectives. For this reason, this study compared ten commonly used CNV detection applications, including CNVnator, ReadDepth, RDXplorer, LUMPY and Control-FREEC, benchmarking the applications by sensitivity, specificity and computational demands. Taking the DGV gold standard variants as a standard dataset, we evaluated the ten applications with real sequencing data at sequencing depths from 5X to 50X. Among the ten methods benchmarked, LUMPY performs the best for both high sensitivity and specificity at each sequencing depth. For the purpose of high specificity, Canvas is also a good choice. If high sensitivity is preferred, CNVnator and RDXplorer are better choices. Additionally, CNVnator and GROM-RD perform well for low-depth sequencing data. Our results provide a comprehensive performance evaluation for these selected CNV detection methods and facilitate future development and improvement in CNV prediction methods.

Genomic incompatibilities in the diploid and tetraploid offspring of the goldfish × common carp cross.

Polyploidy is much rarer in animals than in plants but it is not known why. The outcome of combining two genomes in vertebrates remains unpredictable, especially because polyploidization seldom shows positive effects and more often results in lethal consequences because viable gametes fail to form during meiosis. Fortunately, the goldfish (maternal) × common carp (paternal) hybrids have reproduced successfully up to generation 22, and this hybrid lineage permits an investigation into the genomics of hybridization and tetraploidization. The first two generations of these hybrids are diploids, and subsequent generations are tetraploids. Liver transcriptomes from four generations and their progenitors reveal chimeric genes (>9%) and mutations of orthologous genes. Characterizations of 18 randomly chosen genes from genomic DNA and cDNA confirm the chimera. Some of the chimeric and differentially expressed genes relate to mutagenesis, repair, and cancer-related pathways in 2nF1. Erroneous DNA excision between homologous parental genes may drive the high percentage of chimeric genes, or even more potential mechanisms may result in this phenomenon. Meanwhile, diploid offspring show paternal-biased expression, yet tetraploids show maternal-biased expression. These discoveries reveal that fast and unstable changes are mainly deleterious at the level of transcriptomes although some offspring still survive their genomic abnormalities. In addition, the synthetic effect of genome shock might have resulted in greatly reduced viability of 2nF2 hybrid offspring. The goldfish × common carp hybrids constitute an ideal system for unveiling the consequences of intergenomic interactions in hybrid vertebrate genomes and their fertility.

Comprehensive Assessment of Genotype Imputation Performance.

Genotype imputation is a process of estimating missing ge-notypes from the haplotype or genotype reference panel. It can effectively boost the power of detecting single nucleotide polymorphisms (SNPs) in genome-wide association studies, integrate multi-studies for meta-analysis, and be applied in fine-mapping studies. The performance of genotype imputation is affected by many factors, including software, reference selection, sample size, and SNP density/sequencing coverage. A systematical evaluation of the imputation performance of current popular software will benefit future studies. Here, we evaluate imputation performances of Beagle4.1, IMPUTE2, MACH+Minimac3, and SHAPEIT2+ IM-PUTE2 using test samples of East Asian ancestry and references of the 1000 Genomes Project. The result indicated the accuracy of IMPUTE2 (99.18%) is slightly higher than that of the others (Beagle4.1: 98.94%, MACH+Minimac3: 98.51%, and SHAPEIT2+IMPUTE2: 99.08%). To achieve good and stable imputation quality, the minimum requirement of SNP density needs to be > 200/Mb. The imputation accuracies of IMPUTE2 and Beagle4.1 were under the minor influence of the study sample size. The contribution extent of reference to genotype imputation performance relied on software selection. We assessed the imputation performance on SNPs generated by next-generation whole genome sequencing and found that SNP sets detected by sequencing with 15× depth could be mostly got by imputing from the haplotype reference panel of the 1000 Genomes Project based on SNP data detected by sequencing with 4× depth. All of the imputation software had a weaker performance in low minor allele frequency SNP regions because of the bias of reference or software. In the future, more comprehensive reference panels or new algorithm developments may rise up to this challenge.

MicroRNA 200a inhibits erythroid differentiation by targeting PDCD4 and THRB.

Previous studies on erythropoiesis revealed that microRNAs (miRNAs) play a critical role in erythroid differentiation. Given the abundance of identified miRNAs and the limited understanding of erythroid miRNAs, additional examination is required. Here, two sets of erythroid differentiation miRNome data were analysed to screen for novel erythroid-inhibiting miRNAs. MIR200A was selected based on its pattern of downregulated expression in the miRNome datasets during induction of erythroid differentiation. Overexpression of MIR200A in K562 and TF-1 cells confirmed its inhibitory role in erythroid differentiation. Further in vivo study indicated that overexpression of mir200a inhibited primitive erythropoiesis of zebrafish. Transcriptome analyses after MIR200A overexpression in TF-1 cells indicated a significant role in regulating erythroid function and revealed potential regulation networks. Additionally, bioinformatics and experimental analyses confirmed that PDCD4 (programmed cell death 4) and THRB (thyroid hormone receptor, beta) are both targets of MIR200A-3p. Gain- and loss-of-function studies of PDCD4 and THRB revealed that the two targets were capable of promoting erythroid gene expression. Overall, our results revealed that microRNA 200a inhibits erythroid differentiation by targeting PDCD4 and THRB.

Comparative genomic analysis of N2-fixing and non-N2-fixing Paenibacillus spp.: organization, evolution and expression of the nitrogen fixation genes.

We provide here a comparative genome analysis of 31 strains within the genus Paenibacillus including 11 new genomic sequences of N2-fixing strains. The heterogeneity of the 31 genomes (15 N2-fixing and 16 non-N2-fixing Paenibacillus strains) was reflected in the large size of the shell genome, which makes up approximately 65.2% of the genes in pan genome. Large numbers of transposable elements might be related to the heterogeneity. We discovered that a minimal and compact nif cluster comprising nine genes nifB, nifH, nifD, nifK, nifE, nifN, nifX, hesA and nifV encoding Mo-nitrogenase is conserved in the 15 N2-fixing strains. The nif cluster is under control of a σ(70)-depedent promoter and possesses a GlnR/TnrA-binding site in the promoter. Suf system encoding [Fe-S] cluster is highly conserved in N2-fixing and non-N2-fixing strains. Furthermore, we demonstrate that the nif cluster enabled Escherichia coli JM109 to fix nitrogen. Phylogeny of the concatenated NifHDK sequences indicates that Paenibacillus and Frankia are sister groups. Phylogeny of the concatenated 275 single-copy core genes suggests that the ancestral Paenibacillus did not fix nitrogen. The N2-fixing Paenibacillus strains were generated by acquiring the nif cluster via horizontal gene transfer (HGT) from a source related to Frankia. During the history of evolution, the nif cluster was lost, producing some non-N2-fixing strains, and vnf encoding V-nitrogenase or anf encoding Fe-nitrogenase was acquired, causing further diversification of some strains. In addition, some N2-fixing strains have additional nif and nif-like genes which may result from gene duplications. The evolution of nitrogen fixation in Paenibacillus involves a mix of gain, loss, HGT and duplication of nif/anf/vnf genes. This study not only reveals the organization and distribution of nitrogen fixation genes in Paenibacillus, but also provides insight into the complex evolutionary history of nitrogen fixation.

Genomic Characterization Reveals Insights Into Patulin Biosynthesis and Pathogenicity in Penicillium Species.

Penicillium species are fungal pathogens that infect crop plants worldwide. P. expansum differs from P. italicum and P. digitatum, all major postharvest pathogens of pome and citrus, in that the former is able to produce the mycotoxin patulin and has a broader host range. The molecular basis of host-specificity of fungal pathogens has now become the focus of recent research. The present report provides the whole genome sequence of P. expansum (33.52 Mb) and P. italicum (28.99 Mb) and identifies differences in genome structure, important pathogenic characters, and secondary metabolite (SM) gene clusters in Penicillium species. We identified a total of 55 gene clusters potentially related to secondary metabolism, including a cluster of 15 genes (named PePatA to PePatO), that may be involved in patulin biosynthesis in P. expansum. Functional studies confirmed that PePatL and PePatK play crucial roles in the biosynthesis of patulin and that patulin production is not related to virulence of P. expansum. Collectively, P. expansum contains more pathogenic genes and SM gene clusters, in particular, an intact patulin cluster, than P. italicum or P. digitatum. These findings provide important information relevant to understanding the molecular network of patulin biosynthesis and mechanisms of host-specificity in Penicillium species.

Comparative transcriptome profiling of a rice line carrying Xa39 and its parents triggered by Xanthomonas oryzae pv. oryzae provides novel insights into the broad-spectrum hypersensitive response.

BACKGROUND: Bacterial blight, caused by Xanthomonas oryzae pv. oryzae (Xoo), is a devastating rice disease worldwide. Xa39 is a resistance (R) gene with a broad-spectrum hypersensitive response (BSHR) to Xoo. Nevertheless, the molecular mechanisms of resistance mediated by Xa39 remain unclear. In this study, the transcriptome profiling of a rice line carrying Xa39 and its parents at the early stage of Xoo infection were investigated. RESULTS: A rice introgression line H471 carrying Xa39 exhibited a typical local hypersensitive response phenotype, accompanied by programmed cell death after inoculation with the Xoo Philippines' race 9b. Transcriptome profiling of H471 and its parents at 1 and 2 days post-inoculation was performed using RNA sequencing. In total, 306 differentially expressed genes (DEGs) were identified in H471 compared with its recurrent parent Huang-Hua-Zhan after inoculation with Xoo. Among them, 121 (39.5%) genes, with functional enrichments that were related to defense response, protein amino acid phosphorylation, and apoptosis, were found to be constitutively expressed. The other 185 (60.5%) genes, with GO terms that belonged to defense response, were significantly responsive to Xoo infection in H471. Ten up-regulated and 12 down-regulated genes encoding intracellular immune receptors were identified in H471 compared with Huang-Hua-Zhan. LOC_Os11g37759, which was located in the fine-mapping region harboring Xa39, is a Xa39 candidate gene. The putative BSHR-related co-regulatory networks were constructed using 33 DEGs from four functional groups, including gibberellic acid receptors and brassinosteroid regulators, which were differentially co-expressed with LOC_Os11g37759 in infected H471. Our results indicated that there might be cross-talk between the Xa39-mediated signal transduction cascades and the GA/BR signaling pathway, and that the defense mechanism was related to diverse kinases, transcription factors, post-translational regulation, and R genes. CONCLUSIONS: The present study provides the comprehensive transcriptome profile of a rice introgression line carrying Xa39 and its parents, and identifies a set of DEGs involved in BSHR mediated by Xa39. These data provide novel insights into the regulatory networks of plant disease resistance mediated by R genes, and the identified DEGs will serve as candidates for Xa39 cloning and for further understanding the molecular mechanism of BSHR.

De novo transcriptome analysis of Medicago falcata reveals novel insights about the mechanisms underlying abiotic stress-responsive pathway.

BACKGROUND: The entire world is facing a deteriorating environment. Understanding the mechanisms underlying plant responses to external abiotic stresses is important for breeding stress-tolerant crops and herbages. Phytohormones play critical regulatory roles in plants in the response to external and internal cues to regulate growth and development. Medicago falcata is one of the stress-tolerant candidate leguminous species and is able to fix atmospheric nitrogen. This ability allows leguminous plants to grow in nitrogen deficient soils. METHODS: We performed Illumina sequencing of cDNA prepared from abiotic stress treated M. falcata. Sequencedreads were assembled to provide a transcriptome resource. Transcripts were annotated using BLASTsearches against the NCBI non-redundant database and gene ontology definitions were assigned. Acomparison among the three abiotic stress treated samples was carried out. The expression of transcriptswas confirmed with qRT-PCR. RESULTS: We present an abiotic stress-responsive M. falcata transcriptome using next-generation sequencing data from samples grown under standard, dehydration, high salinity, and cold conditions. We combined reads from all samples and de novo assembled 98,515 transcripts to build the M. falcata gene index. A comprehensive analysis of the transcriptome revealed abiotic stress-responsive mechanisms underlying the metabolism and core signalling components of major phytohormones. We identified nod factor signalling pathways during early symbiotic nodulation that are modified by abiotic stresses. Additionally, a global comparison of homology between the M. falcata and M. truncatula transcriptomes, along with five other leguminous species, revealed a high level of global sequence conservation within the family. CONCLUSIONS: M. falcata is shown to be a model candidate for studying abiotic stress-responsive mechanisms in legumes. This global gene expression analysis provides new insights into the biochemical and molecular mechanisms involved in the acclimation to abiotic stresses. Our data provides many gene candidates that might be used for herbage and crop breeding. Additionally, FalcataBase ( http://bioinformatics.cau.edu.cn/falcata/ ) was built for storing these data.

Genome sequence and transcriptome analyses of the thermophilic zygomycete fungus Rhizomucor miehei.

BACKGROUND: The zygomycete fungi like Rhizomucor miehei have been extensively exploited for the production of various enzymes. As a thermophilic fungus, R. miehei is capable of growing at temperatures that approach the upper limits for all eukaryotes. To date, over hundreds of fungal genomes are publicly available. However, Zygomycetes have been rarely investigated both genetically and genomically. RESULTS: Here, we report the genome of R. miehei CAU432 to explore the thermostable enzymatic repertoire of this fungus. The assembled genome size is 27.6-million-base (Mb) with 10,345 predicted protein-coding genes. Even being thermophilic, the G + C contents of fungal whole genome (43.8%) and coding genes (47.4%) are less than 50%. Phylogenetically, R. miehei is more closerly related to Phycomyces blakesleeanus than to Mucor circinelloides and Rhizopus oryzae. The genome of R. miehei harbors a large number of genes encoding secreted proteases, which is consistent with the characteristics of R. miehei being a rich producer of proteases. The transcriptome profile of R. miehei showed that the genes responsible for degrading starch, glucan, protein and lipid were highly expressed. CONCLUSIONS: The genome information of R. miehei will facilitate future studies to better understand the mechanisms of fungal thermophilic adaptation and the exploring of the potential of R. miehei in industrial-scale production of thermostable enzymes. Based on the existence of a large repertoire of amylolytic, proteolytic and lipolytic genes in the genome, R. miehei has potential in the production of a variety of such enzymes.