Pathogenesis Study Based on High Throughput Single-Cell Sequencing Analysis Reveals Novel Transcriptional Landscape and Heterogeneity of Retinal Cells in Type 2 Diabetic Mice Article Swipe
Tian Niu
,
Junwei Fang
,
X. Shi
,
Mengya Zhao
,
Xindan Xing
,
Yihan Wang
,
Shaopin Zhu
,
Kun Liu
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.2337/figshare.14120015.v1
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.2337/figshare.14120015.v1
Diabetic retinopathy (DR) is the leading cause of acquired blindness in middle-aged people. The complex pathology of DR is difficult to dissect, given the convoluted cytoarchitecture of the retina. Here, we performed single-cell RNA sequencing (scRNA-seq) of retina from type 2 diabetic model induced in leptin receptor-deficient (db/db) and control db/m mice with the aim of elucidating the factors mediating the pathogenesis of DR. We identified eleven cell types and determined cell type-specific expression of DR-associated loci via genome-wide association study-based enrichment analysis. DR also impacted cell type-specific genes and altered cell-cell communication. Based on the scRNA-seq results, retinaldehyde-binding protein 1 (RLBP1) was investigated as a promising therapeutic target for DR. Retinal RLBP1 expression was decreased in diabetes, and its overexpression in Müller glia mitigated DR-associated neurovascular degeneration. These data provide a detailed analysis of the retina under diabetic and normal conditions, revealing new insights into pathogenic factors that may be targeted to treat DR and related dysfunctions.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.2337/figshare.14120015.v1
- OA Status
- gold
- Cited By
- 2
- References
- 1
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- 10
- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4255089737Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.2337/figshare.14120015.v1Digital Object Identifier
- Title
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Pathogenesis Study Based on High Throughput Single-Cell Sequencing Analysis Reveals Novel Transcriptional Landscape and Heterogeneity of Retinal Cells in Type 2 Diabetic MiceWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-03-05Full publication date if available
- Authors
-
Tian Niu, Junwei Fang, X. Shi, Mengya Zhao, Xindan Xing, Yihan Wang, Shaopin Zhu, Kun LiuList of authors in order
- Landing page
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https://doi.org/10.2337/figshare.14120015.v1Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.2337/figshare.14120015.v1Direct OA link when available
- Concepts
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Diabetic retinopathy, Biology, Retina, Pathogenesis, Cell type, Retinal, Cell, Retinal degeneration, Gene, Type 2 diabetes, Genetics, Cell biology, Endocrinology, Diabetes mellitus, Neuroscience, Immunology, BiochemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
- Citations by year (recent)
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2023: 2Per-year citation counts (last 5 years)
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1Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.cell-cell | 91 |
| abstract_inverted_index.decreased | 115 |
| abstract_inverted_index.diabetes, | 117 |
| abstract_inverted_index.difficult | 19 |
| abstract_inverted_index.mediating | 59 |
| abstract_inverted_index.mitigated | 124 |
| abstract_inverted_index.pathology | 15 |
| abstract_inverted_index.performed | 31 |
| abstract_inverted_index.promising | 106 |
| abstract_inverted_index.revealing | 142 |
| abstract_inverted_index.scRNA-seq | 96 |
| abstract_inverted_index.convoluted | 24 |
| abstract_inverted_index.enrichment | 81 |
| abstract_inverted_index.expression | 73, 113 |
| abstract_inverted_index.pathogenic | 146 |
| abstract_inverted_index.sequencing | 34 |
| abstract_inverted_index.(scRNA-seq) | 35 |
| abstract_inverted_index.association | 79 |
| abstract_inverted_index.conditions, | 141 |
| abstract_inverted_index.elucidating | 56 |
| abstract_inverted_index.genome-wide | 78 |
| abstract_inverted_index.middle-aged | 11 |
| abstract_inverted_index.retinopathy | 1 |
| abstract_inverted_index.single-cell | 32 |
| abstract_inverted_index.study-based | 80 |
| abstract_inverted_index.therapeutic | 107 |
| abstract_inverted_index.investigated | 103 |
| abstract_inverted_index.pathogenesis | 61 |
| abstract_inverted_index.DR-associated | 75, 125 |
| abstract_inverted_index.degeneration. | 127 |
| abstract_inverted_index.dysfunctions. | 157 |
| abstract_inverted_index.neurovascular | 126 |
| abstract_inverted_index.type-specific | 72, 87 |
| abstract_inverted_index.</a>cell | 71 |
| abstract_inverted_index.communication. | 92 |
| abstract_inverted_index.overexpression | 120 |
| abstract_inverted_index.types</a> | 68 |
| abstract_inverted_index.cytoarchitecture | 25 |
| abstract_inverted_index.<a>Diabetic | 0 |
| abstract_inverted_index.receptor-deficient | 46 |
| abstract_inverted_index.retinaldehyde-binding | 98 |
| abstract_inverted_index.<a></a><a>determined | 70 |
| abstract_inverted_index.</a><a></a><a>identified | 65 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 94 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.5600000023841858 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.52220272 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |