High-throughput transcriptomics
Abstract High-throughput transcriptomics has revolutionised the field of transcriptome research by offering a cost-effective and powerful screening tool. Standard bulk RNA sequencing (RNA-Seq) enables characterisation of the average expression profiles for individual samples and facilitates identifi...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-11-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-23985-1 |
| _version_ | 1811315276568854528 |
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| author | Nunzio D’Agostino Wenli Li Dapeng Wang |
| author_facet | Nunzio D’Agostino Wenli Li Dapeng Wang |
| author_sort | Nunzio D’Agostino |
| collection | DOAJ |
| description | Abstract High-throughput transcriptomics has revolutionised the field of transcriptome research by offering a cost-effective and powerful screening tool. Standard bulk RNA sequencing (RNA-Seq) enables characterisation of the average expression profiles for individual samples and facilitates identification of the molecular functions associated with genes differentially expressed across conditions. RNA-Seq can also be applied to disentangle splicing variants and discover novel transcripts, thus contributing to a comprehensive understanding of the transcriptome landscape. A closely related technique, single-cell RNA-Seq, has enabled the study of cell-type-specific gene expressions in hundreds to thousands of cells, aiding the exploration of cell heterogeneity. Nowadays, bulk RNA-Seq and single-cell RNA-Seq serve as complementary tools to advance and accelerate the development of transcriptome-based resources. This Collection illustrates how the current global research community makes use of these techniques to address a broad range of questions in life sciences. It demonstrates the usefulness and popularity of high-throughput transcriptomics and presents the best practices and potential issues for the benefit of future end-users. |
| first_indexed | 2024-04-13T11:27:24Z |
| format | Article |
| id | doaj.art-41f2c54df0d144b5b1eda8f31d84260c |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-13T11:27:24Z |
| publishDate | 2022-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-41f2c54df0d144b5b1eda8f31d84260c2022-12-22T02:48:39ZengNature PortfolioScientific Reports2045-23222022-11-011211310.1038/s41598-022-23985-1High-throughput transcriptomicsNunzio D’Agostino0Wenli Li1Dapeng Wang2Department of Agricultural Sciences, University of Naples Federico IIDairy Forage Research Center, USDA-ARSNational Heart and Lung Institute, Imperial College LondonAbstract High-throughput transcriptomics has revolutionised the field of transcriptome research by offering a cost-effective and powerful screening tool. Standard bulk RNA sequencing (RNA-Seq) enables characterisation of the average expression profiles for individual samples and facilitates identification of the molecular functions associated with genes differentially expressed across conditions. RNA-Seq can also be applied to disentangle splicing variants and discover novel transcripts, thus contributing to a comprehensive understanding of the transcriptome landscape. A closely related technique, single-cell RNA-Seq, has enabled the study of cell-type-specific gene expressions in hundreds to thousands of cells, aiding the exploration of cell heterogeneity. Nowadays, bulk RNA-Seq and single-cell RNA-Seq serve as complementary tools to advance and accelerate the development of transcriptome-based resources. This Collection illustrates how the current global research community makes use of these techniques to address a broad range of questions in life sciences. It demonstrates the usefulness and popularity of high-throughput transcriptomics and presents the best practices and potential issues for the benefit of future end-users.https://doi.org/10.1038/s41598-022-23985-1 |
| spellingShingle | Nunzio D’Agostino Wenli Li Dapeng Wang High-throughput transcriptomics Scientific Reports |
| title | High-throughput transcriptomics |
| title_full | High-throughput transcriptomics |
| title_fullStr | High-throughput transcriptomics |
| title_full_unstemmed | High-throughput transcriptomics |
| title_short | High-throughput transcriptomics |
| title_sort | high throughput transcriptomics |
| url | https://doi.org/10.1038/s41598-022-23985-1 |
| work_keys_str_mv | AT nunziodagostino highthroughputtranscriptomics AT wenlili highthroughputtranscriptomics AT dapengwang highthroughputtranscriptomics |