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Diversity,community structure,and quantity of eukaryotic phytoplankton revealed using 18S rRNA and plastid 16S rRNA genes and pigment markers:a case study of the Pearl River Estuary

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Marine Life Science & Technology 2023年第3期5卷 415-430页

作者： Shumin Xu Guihao Li Cui He Yi Huang Dan Yu Huiwen Deng Zhuyin Tong Yichong Wang Christine Dupuy Bangqin Huang Zhuo Shen Jie Xu Jun Gong School of Marine Sciences Sun Yat-Sen University(Zhuhai Campus)and Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 519000China Guangdong Provincial Key Laboratory of Marine Resources and Coastal Engineering Guangzhou 510006China State Key Laboratory of Marine Environmental Science Xiamen UniversityXiamen 361102China BIOFEEL UMRi LIENSsLa Rochelle Université/CNRSLa RochelleFrance Centre for Regional Oceans Department of Civil and Environmental EngineeringFaculty of Science and TechnologyUniversity of MacaoMacaoChina

Understanding consistencies and discrepancies in characterizing diversity and quantity of phytoplankton is essential for better modeling ecosystem change.In this study,eukaryotic phytoplankton in the Pearl River Estuary,South China Sea were investigated using nuclear 18S rRNA and plastid 16S or 23S rRNA genes and pigment analysis.It was found that 18S abundance poorly explained the variations in total chlorophyll a(Chl-a).However,the ratios of log-transformed 18S abundance to Chl-a in the major phytoplankton groups were generally environment dependent,suggesting that the ratio has potential as an indicator of the physiological state of phytoplankton.The richness of 18S-based operational taxonomic units was positively correlated with the richness of 16S-based amplicon sequence variants of the whole phytoplankton community,but insignifcant or weak for individual phytoplankton groups.Overall,the 18S based,rather than the 16S based,community structure had a greater similarity to pigment-based estimations.Relative to the pigment data,the proportion of haptophytes in the 18S dataset,and diatoms and cryptophytes in the 16S dataset,were underestimated.This study highlights that 18S metabarcoding tends to refect biomass-based community organization of eukaryotic phytoplankton.Because there were lower copy numbers of plastid 16S than 18S per genome,metabarcoding of 16S probably approximates cell abundance-based community organization.Changes in biomass organization of the pigment-based community were sensitive to environmental changes.Taken together,multiple methodologies are recommended to be applied to more accurately profle the diversity and community composition of phytoplankton in natural ecosystems.

关键词： Accessory pigments Chloroplast marker gene Metabarcoding Phytoplankton

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Assessment and Optimization of Explainable Machine Learning Models Applied to Transcriptomic Data

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Genomics, Proteomics & Bioinformatics 2022年第5期20卷 899-911页

作者： Yongbing Zhao Jinfeng Shao Yan W.Asmann Department of Quantitative Health Sciences Mayo ClinicJacksonvilleFL 32224USA The Laboratory of Malaria and Vector Research National Institute of Allergy and Infectious DiseasesNational Institutes of HealthRockvilleMD 20852USA

Explainable artificial intelligence aims to interpret how machine learning models make decisions,and many model explainers have been developed in the computer vision field.However,understanding of the applicability of these model explainers to biological data is still lacking.In this study,we comprehensively evaluated multiple explainers by interpreting pre-trained models for predicting tissue types from transcriptomic data and by identifying the top contributing genes from each sample with the greatest impacts on model prediction.To improve the reproducibility and interpretability of results generated by model explainers,we proposed a series of optimization strategies for each explainer on two different model architectures of multilayer perceptron(MLP)and convolutional neural network(CNN).We observed three groups of explainer and model architecture combinations with high reproducibility.Group II,which contains three model explainers on aggregated MLP models,identified top contributing genes in different tissues that exhibited tissue-specific manifestation and were potential cancer biomarkers.In summary,our work provides novel insights and guidance for exploring biological mechanisms using explainable machine learning models.

关键词： Machine learning Model interpretability gene expression marker gene Omics data mining

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Rescue of white egg 1 mutant by introduction of the wildtype Bombyx kynurenine 3-monooxygenase gene

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Insect Science 2007年第2期14卷 85-92页

作者： GUO-XING QUAN ISAO KOBAYASHI KATSURA KOJIMA KEIRO UCHINO TOSHIO KANDA HIDEKI SEZUTSU TORU SHIMADA TOSHIKI TAMURA Transgenic Silkworm Research Center National Institute of Agrobiological Sciences Tsukuba Ibaraki 305-8634 Japan Biomimetic Laboratory National Institute of Agrobiological Sciences Tsukuba Ibaraki 305-8634 Japan Department of Agricultural and Environmental Biology Graduate School of Agricultural and Life Sciences The University of Tokyo Tokyo Japan

In silkworms, the white egg 1 （w-1） mutant, which is characterized by white eyes and white eggs, is deficient in Bombyx kynurenine 3-monooxygenase （KMO） activity. To investigate whether the w-1 mutant phenotype is rescued by introducing the wild-type KMO gene, we constructed transgenic silkworms with the wild-type Bombyx KMO gene under the control of either the cytoplasmic actin gene promoter （A3KMO） or the native KMO gene promoter （KKMO）. We created two transgenic lines with A3KMO and one line with KKMO constructs. The eyes of adults in these lines were brown, and the eggs laid by the transgenic females were also brown. Reverse transcription-polymerase chain reaction（RT-PCR） analysis showed that the A3KMO silkworm lines expressed the transcript in the mid-gut, fat bodies, and Malpighian tubules. The KKMO line expressed the transcript only in the fat bodies and Malpighian tubules. The intensity of eye and egg color in the transgenic lines was proportional to the KMO expression level. Interestingly, transgenic larvae with the A3KMO construct had a light brown larval cuticle, but the KKMO line did not. These results indicate that the wild-type KMO gene can be used as a marker gene for visually screening transgenic silkworms.

关键词： Bombyx mori KMO marker gene transgenic w-1

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ImmuSubset:a database of experimentally validated human and mouse immune cell subsets

ImmuSubset:a database of experimentally validated human and ...

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第十四届全国免疫学学术大会

作者： Yuzhe Hu Huiying Qi Shibin Song Ling Tang Wenling Han Pingzhang Wang Department of Immunology Peking University Health Science Center Peking University Center for Human Disease Genomics Department of Health Informatics and Management Peking University Health Science Center Information and Communication Center Peking University Health Science Center

Many immune cell subsets have been identified in recent years.These subsets are labelled by diffe rent molecular markers and combinations of these markers,and exhibit diversified phenotypes and functions involved in diffe rent physiological and pathological processes.H owever,no existing resource or database has recorded all of these immune cell subsets and relevant information,and the true number of identified immune cell subsets remains unknown.In this study,we present a new database,ImmuSubset,that collects information about experimentally validated human and mouse immune cell subsets.ImmuSubset supports queries by cell type and gene symbol or alias,and thus provides a convenient way to view reported immune cell subsets and information about related maker gene.The current database version covers 16 human and 16 mouse immune cell types,with 2,757 and 2,233 immune cell subsets,respectively,and involves more than 360 and 306 marker genes,respectively.Both T cell subsets are the most abundant among both human and mouse cell types.The database URL is http://***/immusubset.

关键词： Immune cell subset database marker gene immuno-phenotype

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