ABC-seq expands small RNAs content with randomized adapter pools operation Article Swipe
Huahang Yu
,
Mingyu Ye
,
Yingying Guo
,
Yating Sun
,
Ke Cao
,
D. Zhang
,
Feng Chen
,
Yongxi Zhao
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1101/2024.08.30.610480
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1101/2024.08.30.610480
Cellular gene expression is widely regulated by a large number of small RNAs (smRNAs). The ability to in-depth analysis of smRNAs content is vital for comprehensive understanding their architecture and function. However, experimental approaches capable of realizing both high-content and low-byproduct sequencing analysis are lacking. Here, we develop ABC-seq (randomized A dapter pool dimer B locking and C leavage in smRNA sequencing). This method designs randomized adapter pools to recognize more smRNA species. Moreover, it operates two product structure-differentiated enzymatic reactions to maximally eliminate the byproducts of adapter dimers. Using ABC-seq, we detected a broader range of smRNAs including miRNAs, scRNAs, and snoRNAs in rat hypertrophic cardiomyocytes. Upon further analysis of miRNAs, we detected 66 more miRNAs compared to the control method, providing new insights into smRNA-directed gene regulation mechanisms. Furthermore, we revealed cancer drug response -associated smRNAs and uncovered their pivotal role in immune response modulation in non-small cell lung cancer. ABC-seq represents an evolutionary strategy for reshaping the smRNA landscape boundaries and paves the way for a deeper understanding of complex gene regulation networks.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2024.08.30.610480
- https://www.biorxiv.org/content/biorxiv/early/2024/08/30/2024.08.30.610480.full.pdf
- OA Status
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- References
- 44
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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- DOI
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https://doi.org/10.1101/2024.08.30.610480Digital Object Identifier
- Title
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ABC-seq expands small RNAs content with randomized adapter pools operationWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-08-30Full publication date if available
- Authors
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Huahang Yu, Mingyu Ye, Yingying Guo, Yating Sun, Ke Cao, D. Zhang, Feng Chen, Yongxi ZhaoList of authors in order
- Landing page
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https://doi.org/10.1101/2024.08.30.610480Publisher landing page
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https://www.biorxiv.org/content/biorxiv/early/2024/08/30/2024.08.30.610480.full.pdfDirect link to full text PDF
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-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.biorxiv.org/content/biorxiv/early/2024/08/30/2024.08.30.610480.full.pdfDirect OA link when available
- Concepts
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Adapter (computing), Computational biology, Computer science, Biology, Computer hardwareTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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44Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.The | 15 |
| abstract_inverted_index.and | 30, 40, 57, 102, 139, 164 |
| abstract_inverted_index.are | 44 |
| abstract_inverted_index.for | 25, 158, 168 |
| abstract_inverted_index.new | 124 |
| abstract_inverted_index.rat | 105 |
| abstract_inverted_index.the | 85, 120, 160, 166 |
| abstract_inverted_index.two | 77 |
| abstract_inverted_index.way | 167 |
| abstract_inverted_index.RNAs | 13 |
| abstract_inverted_index.This | 63 |
| abstract_inverted_index.Upon | 108 |
| abstract_inverted_index.both | 38 |
| abstract_inverted_index.cell | 150 |
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| abstract_inverted_index.gene | 2, 128, 174 |
| abstract_inverted_index.into | 126 |
| abstract_inverted_index.lung | 151 |
| abstract_inverted_index.more | 71, 116 |
| abstract_inverted_index.pool | 53 |
| abstract_inverted_index.role | 143 |
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| abstract_inverted_index.Using | 90 |
| abstract_inverted_index.dimer | 54 |
| abstract_inverted_index.large | 9 |
| abstract_inverted_index.paves | 165 |
| abstract_inverted_index.pools | 68 |
| abstract_inverted_index.range | 96 |
| abstract_inverted_index.smRNA | 61, 72, 161 |
| abstract_inverted_index.small | 12 |
| abstract_inverted_index.their | 28, 141 |
| abstract_inverted_index.vital | 24 |
| abstract_inverted_index.cancer | 134 |
| abstract_inverted_index.dapter | 52 |
| abstract_inverted_index.deeper | 170 |
| abstract_inverted_index.immune | 145 |
| abstract_inverted_index.method | 64 |
| abstract_inverted_index.miRNAs | 117 |
| abstract_inverted_index.number | 10 |
| abstract_inverted_index.smRNAs | 21, 98, 138 |
| abstract_inverted_index.widely | 5 |
| abstract_inverted_index.ABC-seq | 49, 153 |
| abstract_inverted_index.ability | 16 |
| abstract_inverted_index.adapter | 67, 88 |
| abstract_inverted_index.broader | 95 |
| abstract_inverted_index.cancer. | 152 |
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| abstract_inverted_index.complex | 173 |
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| abstract_inverted_index.designs | 65 |
| abstract_inverted_index.develop | 48 |
| abstract_inverted_index.dimers. | 89 |
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| abstract_inverted_index.leavage | 59 |
| abstract_inverted_index.locking | 56 |
| abstract_inverted_index.method, | 122 |
| abstract_inverted_index.miRNAs, | 100, 112 |
| abstract_inverted_index.pivotal | 142 |
| abstract_inverted_index.product | 78 |
| abstract_inverted_index.scRNAs, | 101 |
| abstract_inverted_index.snoRNAs | 103 |
| abstract_inverted_index.ABC-seq, | 91 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Cellular | 1 |
| abstract_inverted_index.However, | 32 |
| abstract_inverted_index.analysis | 19, 43, 110 |
| abstract_inverted_index.compared | 118 |
| abstract_inverted_index.detected | 93, 114 |
| abstract_inverted_index.in-depth | 18 |
| abstract_inverted_index.insights | 125 |
| abstract_inverted_index.lacking. | 45 |
| abstract_inverted_index.operates | 76 |
| abstract_inverted_index.response | 136, 146 |
| abstract_inverted_index.revealed | 133 |
| abstract_inverted_index.species. | 73 |
| abstract_inverted_index.strategy | 157 |
| abstract_inverted_index.(smRNAs). | 14 |
| abstract_inverted_index.Moreover, | 74 |
| abstract_inverted_index.eliminate | 84 |
| abstract_inverted_index.enzymatic | 80 |
| abstract_inverted_index.function. | 31 |
| abstract_inverted_index.including | 99 |
| abstract_inverted_index.landscape | 162 |
| abstract_inverted_index.maximally | 83 |
| abstract_inverted_index.networks. | 176 |
| abstract_inverted_index.non-small | 149 |
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| abstract_inverted_index.regulation | 129, 175 |
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| abstract_inverted_index.mechanisms. | 130 |
| abstract_inverted_index.Furthermore, | 131 |
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| abstract_inverted_index.evolutionary | 156 |
| abstract_inverted_index.experimental | 33 |
| abstract_inverted_index.high-content | 39 |
| abstract_inverted_index.hypertrophic | 106 |
| abstract_inverted_index.sequencing). | 62 |
| abstract_inverted_index.comprehensive | 26 |
| abstract_inverted_index.low-byproduct | 41 |
| abstract_inverted_index.understanding | 27, 171 |
| abstract_inverted_index.smRNA-directed | 127 |
| abstract_inverted_index.cardiomyocytes. | 107 |
| abstract_inverted_index.structure-differentiated | 79 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5057672960 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 8 |
| corresponding_institution_ids | https://openalex.org/I87445476 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.7599999904632568 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.2418002 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |