Genome Biology最新文献

{"title":"Systematic interrogation of functional genes underlying cholesterol and lipid homeostasis","authors":"Haihuan Shan, Shuangshuang Fan, Quanrun Li, Ruipu Liang, Zhisong Chen, Shengnan Wang, Xiaofeng Wang, Yurong Li, Shuai Chen, Kun Yu, Teng Fei","doi":"10.1186/s13059-025-03531-8","DOIUrl":"https://doi.org/10.1186/s13059-025-03531-8","url":null,"abstract":"Dyslipidemia or hypercholesterolemia are among the main risk factors for cardiovascular diseases. Unraveling the molecular basis of lipid or cholesterol homeostasis would help to identify novel drug targets and develop effective therapeutics. Here, we adopt a systematic approach to catalog the genes underlying lipid and cholesterol homeostasis by combinatorial use of high-throughput CRISPR screening, RNA sequencing, human genetic variant association analysis, and proteomic and metabolomic profiling. Such integrative multi-omics efforts identify gamma-glutamyltransferase GGT7 as an intriguing potential cholesterol and lipid regulator. As a SREBP2-dependent target, GGT7 positively regulates cellular cholesterol levels and affects the expression of several cholesterol metabolism genes. Furthermore, GGT7 interacts with actin-dependent motor protein MYH10 to control low-density lipoprotein cholesterol (LDL-C) uptake into the cells. Genetic ablation of Ggt7 in mice leads to reduced serum cholesterol levels, supporting an in vivo role of Ggt7 during cholesterol homeostasis. Our study not only provides a repertoire of lipid or cholesterol regulatory genes from multiple angles but also reveals a causal link between a gamma-glutamyltransferase and cholesterol metabolism.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"19 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143635702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-task benchmarking of spatially resolved gene expression simulation models","authors":"Xiaoqi Liang, Marni Torkel, Yue Cao, Jean Yee Hwa Yang","doi":"10.1186/s13059-025-03505-w","DOIUrl":"https://doi.org/10.1186/s13059-025-03505-w","url":null,"abstract":"Computational methods for spatially resolved transcriptomics (SRT) are often developed and assessed using simulated data. The effectiveness of these evaluations relies on the ability of simulation methods to accurately reflect experimental data. However, a systematic evaluation framework for spatial simulators is currently lacking. Here, we present SpatialSimBench, a comprehensive evaluation framework that assesses 13 simulation methods using ten distinct STR datasets. We introduce simAdaptor, a tool that extends single-cell simulators by incorporating spatial variables, enabling them to simulate spatial data. SimAdaptor ensures SpatialSimBench is backwards compatible, facilitating direct comparisons between spatially aware simulators and existing non-spatial single-cell simulators through the adaption. Using SpatialSimBench, we demonstrate the feasibility of leveraging existing single-cell simulators for SRT data and highlight performance differences among methods. Additionally, we evaluate the simulation methods based on a total of 35 metrics across data property estimation, various downstream analyses, and scalability. In total, we generated 4550 results from 13 simulation methods, ten spatial datasets, and 35 metrics. Our findings reveal that model estimation can be influenced by distribution assumptions and dataset characteristics. In summary, our evaluation framework provides guidelines for selecting appropriate methods for specific scenarios and informs future method development.\u0000","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"89 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143635704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A special short-wing petal faba genome and genetic dissection of floral and yield-related traits accelerate breeding and improvement of faba bean","authors":"Rong Liu, Chaoqin Hu, Dan Gao, Mengwei Li, Xingxing Yuan, Liyang Chen, Qin Shu, Zonghe Wang, Xin Yang, Zhengming Dai, Haitian Yu, Feng Yang, Aiqing Zheng, Meiyuan Lv, Vanika Garg, Chengzhi Jiao, Hongyan Zhang, Wanwei Hou, Changcai Teng, Xianli Zhou, Chengzhang Du, Chao Xiang, Dongxu Xu, Yongsheng Tang, Annapurna Chitikineni, Yinmei Duan, Fouad Maalouf, Shiv Kumar Agrawal, Libin Wei, Na Zhao, Rutwik Barmukh, Xiang Li, Dong Wang, Hanfeng Ding, Yujiao Liu, Xin Chen, Rajeev K. Varshney, Yuhua He, Xuxiao Zong, Tao Yang","doi":"10.1186/s13059-025-03532-7","DOIUrl":"https://doi.org/10.1186/s13059-025-03532-7","url":null,"abstract":"A comprehensive study of the genome and genetics of superior germplasms is fundamental for crop improvement. As a widely adapted protein crop with high yield potential, the improvement in breeding and development of the seeds industry of faba bean have been greatly hindered by its giant genome size and high outcrossing rate. To fully explore the genomic diversity and genetic basis of important agronomic traits, we first generate a de novo genome assembly and perform annotation of a special short-wing petal faba bean germplasm (VF8137) exhibiting a low outcrossing rate. Comparative genome and pan-genome analyses reveal the genome evolution characteristics and unique pan-genes among the three different faba bean genomes. In addition, the genome diversity of 558 accessions of faba bean germplasm reveals three distinct genetic groups and remarkable genetic differences between the southern and northern germplasms. Genome-wide association analysis identifies several candidate genes associated with adaptation- and yield-related traits. We also identify one candidate gene related to short-wing petals by combining quantitative trait locus mapping and bulked segregant analysis. We further elucidate its function through multiple lines of evidence from functional annotation, sequence variation, expression differences, and protein structure variation. Our study provides new insights into the genome evolution of Leguminosae and the genomic diversity of faba bean. It offers valuable genomic and genetic resources for breeding and improvement of faba bean.\u0000","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"17 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143635701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring and mitigating shortcomings in single-cell differential expression analysis with a new statistical paradigm","authors":"Chih-Hsuan Wu, Xiang Zhou, Mengjie Chen","doi":"10.1186/s13059-025-03525-6","DOIUrl":"https://doi.org/10.1186/s13059-025-03525-6","url":null,"abstract":"Differential expression analysis is pivotal in single-cell transcriptomics for unraveling cell-type–specific responses to stimuli. While numerous methods are available to identify differentially expressed genes in single-cell data, recent evaluations of both single-cell–specific methods and methods adapted from bulk studies have revealed significant shortcomings in performance. In this paper, we dissect the four major challenges in single-cell differential expression analysis: excessive zeros, normalization, donor effects, and cumulative biases. These “curses” underscore the limitations and conceptual pitfalls in existing workflows. To address the limitations of current single-cell differential expression analysis methods, we propose GLIMES, a statistical framework that leverages UMI counts and zero proportions within a generalized Poisson/Binomial mixed-effects model to account for batch effects and within-sample variation. We rigorously benchmarked GLIMES against six existing differential expression methods using three case studies and simulations across different experimental scenarios, including comparisons across cell types, tissue regions, and cell states. Our results demonstrate that GLIMES is more adaptable to diverse experimental designs in single-cell studies and effectively mitigates key shortcomings of current approaches, particularly those related to normalization procedures. By preserving biologically meaningful signals, GLIMES offers improved performance in detecting differentially expressed genes. By using absolute RNA expression rather than relative abundance, GLIMES improves sensitivity, reduces false discoveries, and enhances biological interpretability. This paradigm shift challenges existing workflows and highlights the need for careful consideration of normalization strategies, ultimately paving the way for more accurate and robust single-cell transcriptomic analyses.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"61 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143635703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The haplotype-resolved genome assembly of an ancient citrus variety provides insights into the domestication history and fruit trait formation of loose-skin mandarins","authors":"Minqiang Yin, Xiaochan Song, Chao He, Xiyuan Li, Mengyuan Li, Jiangbo Li, Hao Wu, Chuanwu Chen, Li Zhang, Zhenmei Cai, Liqing Lu, Yanhui Xu, Xin Wang, Hualin Yi, Juxun Wu","doi":"10.1186/s13059-025-03535-4","DOIUrl":"https://doi.org/10.1186/s13059-025-03535-4","url":null,"abstract":"Loose-skin mandarins (LSMs) are among the oldest domesticated horticultural crops, yet their domestication history and the genetic basis underlying the formation of key selected traits remain unclear. We provide a chromosome-scale and haplotype-resolved assembly for the ancient Chinese citrus variety Nanfengmiju tangerine. Through the integration of 77 resequenced and 114 published citrus germplasm genomes, we categorize LSMs into 12 distinct groups based on population genomic analyses. We infer that the ancestors of modern cultivated mandarins diverged from wild mandarins in Daoxian approximately 500,000 years ago, when they entered the Yangtze and Pearl River Basins. There, they were domesticated into four ancient cultivation groups, forming the cornerstone of modern Chinese LSM cultivation. We identify selective sweeps underlying quantitative trait loci and genes related to important fruit quality traits, including sweetness and size. We reveal that the co-selection of sugar transporter and metabolism genes are associated with increased fruit sweetness. Significant alterations in the auxin and gibberellin signaling networks may contribute to the enlargement of LSM fruits. We also provide a comprehensive, high-spatiotemporal-resolution atlas of allelic gene expression during citrus fruit development. We detect 5890 allele pairs showing specific expression patterns and a significant increase in variation levels. Our study provides valuable genomic resources and further revises the origin and domestication history of LSMs, offering insights for genetic improvement of citrus plants.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"89 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143635692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Widespread impact of transposable elements on the evolution of post-transcriptional regulation in the cotton genus Gossypium","authors":"Xuehan Tian, Ruipeng Wang, Zhenping Liu, Sifan Lu, Xinyuan Chen, Zeyu Zhang, Fang Liu, Hongbin Li, Xianlong Zhang, Maojun Wang","doi":"10.1186/s13059-025-03534-5","DOIUrl":"https://doi.org/10.1186/s13059-025-03534-5","url":null,"abstract":"Transposable element (TE) expansion has long been known to mediate genome evolution and phenotypic diversity in organisms, but its impact on the evolution of post-transcriptional regulation following species divergence remains unclear. To address this issue, we perform long-read direct RNA sequencing, polysome profiling sequencing, and small RNA sequencing in the cotton genus Gossypium, the species of which range more than three folds in genome size. We find that TE expansion contributes to the turnover of transcription splicing sites and regulatory sequences, leading to changes in alternative splicing patterns and the expression levels of orthologous genes. We also find that TE-derived upstream open reading frames and microRNAs serve as regulatory elements mediating differences in the translation levels of orthologous genes. We further identify genes that exhibit lineage-specific divergence at the transcriptional, splicing, and translational levels, and showcase the high flexibility of gene expression regulation in the evolutionary process. Our work highlights the significant role of TE in driving post-transcriptional regulation divergence in the cotton genus. It offers insights for deciphering the evolutionary mechanisms of cotton species and the formation of biological diversity.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"16 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143635706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients","authors":"Yered Pita-Juarez, Dimitra Karagkouni, Nikolaos Kalavros, Johannes C. Melms, Sebastian Niezen, Toni M. Delorey, Adam L. Essene, Olga R. Brook, Deepti Pant, Disha Skelton-Badlani, Pourya Naderi, Pinzhu Huang, Liuliu Pan, Tyler Hether, Tallulah S. Andrews, Carly G. K. Ziegler, Jason Reeves, Andriy Myloserdnyy, Rachel Chen, Andy Nam, Stefan Phelan, Yan Liang, Mark Gregory, Shanshan He, Michael Patrick, Tushar Rane, Aster Wardhani, Amit Dipak Amin, Jana Biermann, Hanina Hibshoosh, Molly Veregge, Zachary Kramer, Christopher Jacobs, Yusuf Yalcin, Devan Phillips, Michal Slyper, Ayshwarya Subramanian, Orr Ashenberg, Zohar Bloom-Ackermann, Victoria M. Tran, James Gomez, Alexander Sturm, Shuting Zhang, Stephen J. Fleming, Sarah Warren, Joseph Beechem, Deborah Hung, Mehrtash Babadi, Robert F. Padera, Sonya A. MacParland, Gary D. Bader, Nasser Imad, Isaac H. Solomon, Eric Miller, Stefan Riedel, Caroline B. M. Porter, Alexandra-Chloé Villani, Linus T.-Y. Tsai, Winston Hide, Gyongyi Szabo,..","doi":"10.1186/s13059-025-03499-5","DOIUrl":"https://doi.org/10.1186/s13059-025-03499-5","url":null,"abstract":"The molecular underpinnings of organ dysfunction in severe COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we perform single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identify hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells, and a central role in a pro-fibrotic TGFβ signaling cell–cell communications network. Integrated analysis and comparisons with healthy controls reveal extensive changes in the cellular composition and expression states in COVID-19 liver, providing the underpinning of hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis characteristic of COVID-19 cholangiopathy. We also observe Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition is dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"8 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143618471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"mRNA m6A regulates gene expression via H3K4me3 shift in 5’ UTR","authors":"Yuna Yang, Yuqing Huang, Tian Wang, Song Li, Jiafu Jiang, Sumei Chen, Fadi Chen, Likai Wang","doi":"10.1186/s13059-025-03515-8","DOIUrl":"https://doi.org/10.1186/s13059-025-03515-8","url":null,"abstract":"N6-methyladenosine (m6A) is a prevalent and conserved RNA modification in eukaryotes. While its roles in the 3’ untranslated regions (3’ UTR) are well-studied, its role in the 5' UTR and its relationship with histone modifications remain underexplored. We demonstrate that m6A methylation in the 5’ UTR of mRNA triggers a downstream shift in H3K4me3 modification. This regulatory mechanism is conserved in Arabidopsis, rice, and chrysanthemum. The observed shift in H3K4me3 is genetically controlled by m6A modifiers and influences gene expression. MTA, the m6A methylase, preferentially binds to phosphorylated serine 5 (Ser5P)-CTD of RNA Pol II during transcription, leading to the displacement of ATX1, the H3K4me3 methylase. This dynamic binding of MTA and ATX1 to RNA Pol II ultimately results in the shift of H3K4me3 modification. Genetic evidence demonstrates that m6A in the 5' UTR controls H3K4me3 shift, thereby affecting SEDOHEPTULOSE-BISPHOSPHATASE expression and leaf senescence. Our study provides new insights into the roles of m6A modification and its crosstalk with histone modification in 5’ UTRs, shedding light on the mechanism of m6A-mediated gene expression regulation.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"22 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143599898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrative phenomics, metabolomics and genomics analysis provides new insights for deciphering the genetic basis of metabolism in polished rice","authors":"Hui Feng, Yufei Li, Guoxin Dai, Zhuang Yang, Jingyan Song, Bingjie Lu, Yuan Gao, Yongqi Chen, Jiawei Shi, Luis A. J. Mur, Lejun Yu, Jie Luo, Wanneng Yang","doi":"10.1186/s13059-025-03513-w","DOIUrl":"https://doi.org/10.1186/s13059-025-03513-w","url":null,"abstract":"Metabolomics is one of the most widely used omics tools for deciphering the functional networks of the metabolites for crop improvement. However, it is technically demanding and costly. We propose a relatively inexpensive approach for metabolomics analysis in which metabolomics is combined with hyperspectral imaging via machine learning. This approach can be used to target important steps in flavonoid and lipid biosynthesis in rice. We extract 1848 hyperspectral indices and 887 metabolites from polished grains of 533 Oryza sativa accessions. Hyperspectral indices are then linked to metabolites through correlation analysis and modelling. Based on this, a total of 554 metabolites and 1313 hyperspectral indices are identified for further genome-wide association study (GWAS). By GWAS, we detect 17,509 significant locus-trait associations with 2882 single nucleotide polymorphisms (SNPs). Colocalization analysis links these SNPs to the corresponding metabolites and hyperspectral indices. We detect 6415 pairs of metabolites and hyperspectral indices within a linkage disequilibrium of 300 kb in the Oryza sativa genome. We then characterize 1761 candidate genes colocalized to these loci by transcriptomic analysis. We further verify novel candidate genes encoding a novel flavonoid (LOC_Os09g18450) and a flavonoid/lipid (LOC_Os07g11020) respectively by gene editing and overexpression in rice. Our findings indicate that hyperspectral imaging combined with machine learning methods could serve as a powerful tool for quickly and inexpensively assessing crop metabolites.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"14 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143608417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-cell RNA-seq data have prevalent blood contamination but can be rescued by Originator, a computational tool separating single-cell RNA-seq by genetic and contextual information","authors":"Thatchayut Unjitwattana, Qianhui Huang, Yiwen Yang, Leyang Tao, Youqi Yang, Mengtian Zhou, Yuheng Du, Lana X. Garmire","doi":"10.1186/s13059-025-03495-9","DOIUrl":"https://doi.org/10.1186/s13059-025-03495-9","url":null,"abstract":"Single-cell RNA sequencing (scRNA-seq) data from complex human tissues have prevalent blood cell contamination during the sample preparation process. They may also comprise cells of different genetic makeups. We propose a new computational framework, Originator, which deciphers single cells by genetic origin and separates immune cells of blood contamination from those of expected tissue-resident cells. We demonstrate the accuracy of Originator at separating immune cells from the blood and tissue as well as cells of different genetic origins, using a variety of artificially mixed and real datasets, including pancreatic cancer and placentas as examples.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"40 1","pages":""},"PeriodicalIF":12.3,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143589834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}