GigaScience最新文献

{"title":"Improved integration of single-cell transcriptome data demonstrates common and unique signatures of heart failure in mice and humans","authors":"Mariano Ruz Jurado, Lukas S Tombor, Mani Arsalan, Tomas Holubec, Fabian Emrich, Thomas Walther, Wesley Abplanalp, Ariane Fischer, Andreas M Zeiher, Marcel H Schulz, Stefanie Dimmeler, David John","doi":"10.1093/gigascience/giae011","DOIUrl":"https://doi.org/10.1093/gigascience/giae011","url":null,"abstract":"Background Cardiovascular research heavily relies on mouse (Mus musculus) models to study disease mechanisms and to test novel biomarkers and medications. Yet, applying these results to patients remains a major challenge and often results in noneffective drugs. Therefore, it is an open challenge of translational science to develop models with high similarities and predictive value. This requires a comparison of disease models in mice with diseased tissue derived from humans. Results To compare the transcriptional signatures at single-cell resolution, we implemented an integration pipeline called OrthoIntegrate, which uniquely assigns orthologs and therewith merges single-cell RNA sequencing (scRNA-seq) RNA of different species. The pipeline has been designed to be as easy to use and is fully integrable in the standard Seurat workflow. We applied OrthoIntegrate on scRNA-seq from cardiac tissue of heart failure patients with reduced ejection fraction (HFrEF) and scRNA-seq from the mice after chronic infarction, which is a commonly used mouse model to mimic HFrEF. We discovered shared and distinct regulatory pathways between human HFrEF patients and the corresponding mouse model. Overall, 54% of genes were commonly regulated, including major changes in cardiomyocyte energy metabolism. However, several regulatory pathways (e.g., angiogenesis) were specifically regulated in humans. Conclusions The demonstration of unique pathways occurring in humans indicates limitations on the comparability between mice models and human HFrEF and shows that results from the mice model should be validated carefully. OrthoIntegrate is publicly accessible (https://github.com/MarianoRuzJurado/OrthoIntegrate) and can be used to integrate other large datasets to provide a general comparison of models with patient data.","PeriodicalId":12581,"journal":{"name":"GigaScience","volume":"103 1","pages":""},"PeriodicalIF":9.2,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140599512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pangenome databases improve host removal and mycobacteria classification from clinical metagenomic data","authors":"Michael B Hall, Lachlan J M Coin","doi":"10.1093/gigascience/giae010","DOIUrl":"https://doi.org/10.1093/gigascience/giae010","url":null,"abstract":"Background Culture-free real-time sequencing of clinical metagenomic samples promises both rapid pathogen detection and antimicrobial resistance profiling. However, this approach introduces the risk of patient DNA leakage. To mitigate this risk, we need near-comprehensive removal of human DNA sequences at the point of sequencing, typically involving the use of resource-constrained devices. Existing benchmarks have largely focused on the use of standardized databases and largely ignored the computational requirements of depletion pipelines as well as the impact of human genome diversity. Results We benchmarked host removal pipelines on simulated and artificial real Illumina and Nanopore metagenomic samples. We found that construction of a custom kraken database containing diverse human genomes results in the best balance of accuracy and computational resource usage. In addition, we benchmarked pipelines using kraken and minimap2 for taxonomic classification of Mycobacterium reads using standard and custom databases. With a database representative of the Mycobacterium genus, both tools obtained improved specificity and sensitivity, compared to the standard databases for classification of Mycobacterium tuberculosis. Computational efficiency of these custom databases was superior to most standard approaches, allowing them to be executed on a laptop device. Conclusions Customized pangenome databases provide the best balance of accuracy and computational efficiency when compared to standard databases for the task of human read removal and M. tuberculosis read classification from metagenomic samples. Such databases allow for execution on a laptop, without sacrificing accuracy, an especially important consideration in low-resource settings. We make all customized databases and pipelines freely available.","PeriodicalId":12581,"journal":{"name":"GigaScience","volume":"244 1","pages":""},"PeriodicalIF":9.2,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140599486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A multi-omics data analysis workflow packaged as a FAIR Digital Object","authors":"Anna Niehues, Casper de Visser, Fiona A Hagenbeek, Purva Kulkarni, René Pool, Naama Karu, Alida S D Kindt, Gurnoor Singh, Robert R J M Vermeiren, Dorret I Boomsma, Jenny van Dongen, Peter A C ’t Hoen, Alain J van Gool","doi":"10.1093/gigascience/giad115","DOIUrl":"https://doi.org/10.1093/gigascience/giad115","url":null,"abstract":"Background Applying good data management and FAIR (Findable, Accessible, Interoperable, and Reusable) data principles in research projects can help disentangle knowledge discovery, study result reproducibility, and data reuse in future studies. Based on the concepts of the original FAIR principles for research data, FAIR principles for research software were recently proposed. FAIR Digital Objects enable discovery and reuse of Research Objects, including computational workflows for both humans and machines. Practical examples can help promote the adoption of FAIR practices for computational workflows in the research community. We developed a multi-omics data analysis workflow implementing FAIR practices to share it as a FAIR Digital Object. Findings We conducted a case study investigating shared patterns between multi-omics data and childhood externalizing behavior. The analysis workflow was implemented as a modular pipeline in the workflow manager Nextflow, including containers with software dependencies. We adhered to software development practices like version control, documentation, and licensing. Finally, the workflow was described with rich semantic metadata, packaged as a Research Object Crate, and shared via WorkflowHub. Conclusions Along with the packaged multi-omics data analysis workflow, we share our experiences adopting various FAIR practices and creating a FAIR Digital Object. We hope our experiences can help other researchers who develop omics data analysis workflows to turn FAIR principles into practice.","PeriodicalId":12581,"journal":{"name":"GigaScience","volume":"8 1","pages":""},"PeriodicalIF":9.2,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139463300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Disentangling river and swamp buffalo genetic diversity: initial insights from the 1000 Buffalo Genomes Project.","authors":"Paulene S Pineda, Ester B Flores, Lilian P Villamor, Connie Joyce M Parac, Mehar S Khatkar, Hien To Thu, Timothy P L Smith, Benjamin D Rosen, Paolo Ajmone-Marsan, Licia Colli, John L Williams, Wai Yee Low","doi":"10.1093/gigascience/giae053","DOIUrl":"10.1093/gigascience/giae053","url":null,"abstract":"<p><p>More people in the world depend on water buffalo for their livelihoods than on any other domesticated animals, but its genetics is still not extensively explored. The 1000 Buffalo Genomes Project (1000BGP) provides genetic resources for global buffalo population study and tools to breed more sustainable and productive buffaloes. Here we report the most contiguous swamp buffalo genome assembly (PCC_UOA_SB_1v2) with substantial resolution of telomeric and centromeric repeats, ∼4-fold more contiguous than the existing reference river buffalo assembly and exceeding a recently published male swamp buffalo genome. This assembly was used along with the current reference to align 140 water buffalo short-read sequences and produce a public genetic resource with an average of ∼41 million single nucleotide polymorphisms per swamp and river buffalo genome. Comparison of the swamp and river buffalo sequences showed ∼1.5% genetic differences, and estimated divergence time occurred 3.1 million years ago (95% CI, 2.6-4.9). The open science model employed in the 1000BGP provides a key genomic resource and tools for a species with global economic relevance.</p>","PeriodicalId":12581,"journal":{"name":"GigaScience","volume":"13 ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11382405/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142153663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CoCoPyE: feature engineering for learning and prediction of genome quality indices.","authors":"Niklas Birth, Nicolina Leppich, Julia Schirmacher, Nina Andreae, Rasmus Steinkamp, Matthias Blanke, Peter Meinicke","doi":"10.1093/gigascience/giae079","DOIUrl":"https://doi.org/10.1093/gigascience/giae079","url":null,"abstract":"<p><strong>Background: </strong>The exploration of the microbial world has been greatly advanced by the reconstruction of genomes from metagenomic sequence data. However, the rapidly increasing number of metagenome-assembled genomes has also resulted in a wide variation in data quality. It is therefore essential to quantify the achieved completeness and possible contamination of a reconstructed genome before it is used in subsequent analyses. The classical approach for the estimation of quality indices solely relies on a relatively small number of universal single-copy genes. Recent tools try to extend the genomic coverage of estimates for an increased accuracy.</p><p><strong>Results: </strong>We developed CoCoPyE, a fast tool based on a novel 2-stage feature extraction and transformation scheme. First, it identifies genomic markers and then refines the marker-based estimates with a machine learning approach. In our simulation studies, CoCoPyE showed a more accurate prediction of quality indices than the existing tools. While the CoCoPyE web server offers an easy way to try out the tool, the freely available Python implementation enables integration into existing genome reconstruction pipelines.</p><p><strong>Conclusions: </strong>CoCoPyE provides a new approach to assess the quality of genome data. It complements and improves existing tools and may help researchers to better distinguish between low-quality draft and high-quality genome assemblies in metagenome sequencing projects.</p>","PeriodicalId":12581,"journal":{"name":"GigaScience","volume":"13 ","pages":""},"PeriodicalIF":11.8,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11503480/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142498590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data processing solutions to render metabolomics more quantitative: case studies in food and clinical metabolomics using Metabox 2.0.","authors":"Kwanjeera Wanichthanarak, Ammarin In-On, Sili Fan, Oliver Fiehn, Arporn Wangwiwatsin, Sakda Khoomrung","doi":"10.1093/gigascience/giae005","DOIUrl":"10.1093/gigascience/giae005","url":null,"abstract":"<p><p>In classic semiquantitative metabolomics, metabolite intensities are affected by biological factors and other unwanted variations. A systematic evaluation of the data processing methods is crucial to identify adequate processing procedures for a given experimental setup. Current comparative studies are mostly focused on peak area data but not on absolute concentrations. In this study, we evaluated data processing methods to produce outputs that were most similar to the corresponding absolute quantified data. We examined the data distribution characteristics, fold difference patterns between 2 metabolites, and sample variance. We used 2 metabolomic datasets from a retail milk study and a lupus nephritis cohort as test cases. When studying the impact of data normalization, transformation, scaling, and combinations of these methods, we found that the cross-contribution compensating multiple standard normalization (ccmn) method, followed by square root data transformation, was most appropriate for a well-controlled study such as the milk study dataset. Regarding the lupus nephritis cohort study, only ccmn normalization could slightly improve the data quality of the noisy cohort. Since the assessment accounted for the resemblance between processed data and the corresponding absolute quantified data, our results denote a helpful guideline for processing metabolomic datasets within a similar context (food and clinical metabolomics). Finally, we introduce Metabox 2.0, which enables thorough analysis of metabolomic data, including data processing, biomarker analysis, integrative analysis, and data interpretation. It was successfully used to process and analyze the data in this study. An online web version is available at http://metsysbio.com/metabox.</p>","PeriodicalId":12581,"journal":{"name":"GigaScience","volume":"13 ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10941642/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140131178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"De novo assembly and characterization of a highly degenerated ZW sex chromosome in the fish Megaleporinus macrocephalus.","authors":"Carolina Heloisa Souza-Borges, Ricardo Utsunomia, Alessandro M Varani, Marcela Uliano-Silva, Lieschen Valeria G Lira, Arno J Butzge, John F Gomez Agudelo, Shisley Manso, Milena V Freitas, Raquel B Ariede, Vito A Mastrochirico-Filho, Carolina Penaloza, Agustín Barria, Fábio Porto-Foresti, Fausto Foresti, Ricardo Hattori, Yann Guiguen, Ross D Houston, Diogo Teruo Hashimoto","doi":"10.1093/gigascience/giae085","DOIUrl":"10.1093/gigascience/giae085","url":null,"abstract":"<p><strong>Background: </strong>Megaleporinus macrocephalus (piauçu) is a Neotropical fish within Characoidei that presents a well-established heteromorphic ZZ/ZW sex determination system and thus constitutes a good model for studying W and Z chromosomes in fishes. We used PacBio reads and Hi-C to assemble a chromosome-level reference genome for M. macrocephalus. We generated family segregation information to construct a genetic map, pool sequencing of males and females to characterize its sex system, and RNA sequencing to highlight candidate genes of M. macrocephalus sex determination.</p><p><strong>Results: </strong>The reference genome of M. macrocephalus is 1,282,030,339 bp in length and has a contig and scaffold N50 of 5.0 Mb and 45.03 Mb, respectively. In the sex chromosome, based on patterns of recombination suppression, coverage, FST, and sex-specific SNPs, we distinguished a putative W-specific region that is highly differentiated, a region where Z and W still share some similarities and is undergoing degeneration, and the PAR. The sex chromosome gene repertoire includes genes from the TGF-β family (amhr2, bmp7) and the Wnt/β-catenin pathway (wnt4, wnt7a), some of which are differentially expressed.</p><p><strong>Conclusions: </strong>The chromosome-level genome of piauçu exhibits high quality, establishing a valuable resource for advancing research within the group. Our discoveries offer insights into the evolutionary dynamics of Z and W sex chromosomes in fish, emphasizing ongoing degenerative processes and indicating complex interactions between Z and W sequences in specific genomic regions. Notably, amhr2 and bmp7 are potential candidate genes for sex determination in M. macrocephalus.</p>","PeriodicalId":12581,"journal":{"name":"GigaScience","volume":"13 ","pages":""},"PeriodicalIF":11.8,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11590113/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142715761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Functional annotation of regulatory elements in rainbow trout uncovers roles of the epigenome in genetic selection and genome evolution.","authors":"Mohamed Salem, Rafet Al-Tobasei, Ali Ali, Liqi An, Ying Wang, Xuechen Bai, Ye Bi, Huaijun Zhou","doi":"10.1093/gigascience/giae092","DOIUrl":"10.1093/gigascience/giae092","url":null,"abstract":"<p><p>Rainbow trout (RBT) has gained widespread attention as a biological model across various fields and has been rapidly adopted for aquaculture and recreational purposes on 6 continents. Despite significant efforts to develop genome sequences for RBT, the functional genomic basis of RBT's environmental, phenotypic, and evolutionary variations still requires epigenome reference annotations. This study has produced a comprehensive catalog and epigenome annotation tracks of RBT, detecting gene regulatory elements, including chromatin histone modifications, chromatin accessibility, and DNA methylation. By integrating chromatin immunoprecipitation sequencing, ATAC sequencing, Methyl Mini-seq, and RNA sequencing data, this new regulatory element catalog has helped to characterize the epigenome dynamics and its correlation with gene expression. The study has also identified potential causal variants and transcription factors regulating complex domestication phenotypic traits. This research also provides valuable insights into the epigenome's role in gene evolution and the mechanism of duplicate gene retention 100 million years after RBT whole-genome duplication and during re-diploidization. The newly developed epigenome annotation maps are among the first in fish and are expected to enhance the accuracy and efficiency of genomic studies and applications, including genome-wide association studies, causative variation identification, and genomic selection in RBT and fish comparative genomics.</p>","PeriodicalId":12581,"journal":{"name":"GigaScience","volume":"13 ","pages":""},"PeriodicalIF":11.8,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11629980/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142828078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ntsm: an alignment-free, ultra-low-coverage, sequencing technology agnostic, intraspecies sample comparison tool for sample swap detection.","authors":"Justin Chu, Jiazhen Rong, Xiaowen Feng, Heng Li","doi":"10.1093/gigascience/giae024","DOIUrl":"10.1093/gigascience/giae024","url":null,"abstract":"<p><strong>Background: </strong>Due to human error, sample swapping in large cohort studies with heterogeneous data types (e.g., mix of Oxford Nanopore Technologies, Pacific Bioscience, Illumina data, etc.) remains a common issue plaguing large-scale studies. At present, all sample swapping detection methods require costly and unnecessary (e.g., if data are only used for genome assembly) alignment, positional sorting, and indexing of the data in order to compare similarly. As studies include more samples and new sequencing data types, robust quality control tools will become increasingly important.</p><p><strong>Findings: </strong>The similarity between samples can be determined using indexed k-mer sequence variants. To increase statistical power, we use coverage information on variant sites, calculating similarity using a likelihood ratio-based test. Per sample error rate, and coverage bias (i.e., missing sites) can also be estimated with this information, which can be used to determine if a spatially indexed principal component analysis (PCA)-based prescreening method can be used, which can greatly speed up analysis by preventing exhaustive all-to-all comparisons.</p><p><strong>Conclusions: </strong>Because this tool processes raw data, is faster than alignment, and can be used on very low-coverage data, it can save an immense degree of computational resources in standard quality control (QC) pipelines. It is robust enough to be used on different sequencing data types, important in studies that leverage the strengths of different sequencing technologies. In addition to its primary use case of sample swap detection, this method also provides information useful in QC, such as error rate and coverage bias, as well as population-level PCA ancestry analysis visualization.</p>","PeriodicalId":12581,"journal":{"name":"GigaScience","volume":"13 ","pages":""},"PeriodicalIF":11.8,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11148594/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141237337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Near telomere-to-telomere genome assembly of Mongolian cattle: implications for population genetic variation and beef quality.","authors":"Rina Su, Hao Zhou, Wenhao Yang, Sorgog Moqir, Xiji Ritu, Lei Liu, Ying Shi, Ai Dong, Menghe Bayier, Yibu Letu, Xin Manxi, Hasi Chulu, Narenhua Nasenochir, He Meng, Muren Herrid","doi":"10.1093/gigascience/giae099","DOIUrl":"10.1093/gigascience/giae099","url":null,"abstract":"<p><strong>Background: </strong>Mongolian cattle, a unique breed indigenous to China, represent valuable genetic resources and serve as important sources of meat and milk. However, there is a lack of high-quality genomes in cattle, which limits biological research and breeding improvement.</p><p><strong>Findings: </strong>In this study, we conducted whole-genome sequencing on a Mongolian bull. This effort yielded a 3.1 Gb Mongolian cattle genome sequence, with a BUSCO integrity assessment of 95.9%. The assembly achieved both contig N50 and scaffold N50 values of 110.9 Mb, with only 3 gaps identified across the entire genome. Additionally, we successfully assembled the Y chromosome among the 31 chromosomes. Notably, 3 chromosomes were identified as having telomeres at both ends. The annotation data include 54.31% repetitive sequences and 29,794 coding genes. Furthermore, a population genetic variation analysis was conducted on 332 individuals from 56 breeds, through which we identified variant loci and potentially discovered genes associated with the formation of marbling patterns in beef, predominantly located on chromosome 12.</p><p><strong>Conclusions: </strong>This study produced a genome with high continuity, completeness, and accuracy, marking the first assembly and annotation of a near telomere-to-telomere genome in cattle. Based on this, we generated a variant database comprising 332 individuals. The assembly of the genome and the analysis of population variants provide significant insights into cattle evolution and enhance our understanding of breeding selection.</p>","PeriodicalId":12581,"journal":{"name":"GigaScience","volume":"13 ","pages":""},"PeriodicalIF":11.8,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11653892/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142853779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}