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RNA sequencing: advances, challenges and opportunities
Open accessAbstract
In the few years since its initial application, massively parallel cDNA sequencing, or RNA-seq, has allowed many advances in the characterization and quantification of transcriptomes. Recently, several developments in RNA-seq methods have provided an even more complete characterization of RNA transcripts. These developments include improvements in transcription start site mapping, strand-specific measurements, gene fusion detection, small RNA characterization and detection of alternative splicing events. Ongoing developments promise further advances in the application of RNA-seq, particularly direct RNA sequencing and approaches that allow RNA quantification from very small amounts of cellular materials.
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“RNA deep-sequencing (RNA-seq) provides a powerful tool to decipher global gene expression patterns far beyond the limitations of microarrays, including an unprecedented capability to discover novel genes, alternative transcript variants, chimeric transcripts, and expressed sequence variants as well as allele-specific expression [8–12].”
From Comparison of RNA-seq and microarray-based models for clinical endpoint prediction (2015) · cites this paper as [10]
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MethodComprehensive Analysis of Transcriptome Sequencing Data in the Lung Tissues of COPD Subjects
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“Background and cross-hybridization are not issues in RNA-seq and the technology can quantify both lowly and highly abundant transcripts [11].”
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BackgroundTranscriptomic responses to environmental change in fishes: Insights from RNA sequencing
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“For further detail about technical and analytical issues surrounding RNA-seq experiments in general, we refer the reader to several discussions on the topic (Fang and Cui 2011; Ozsolak and Milos 2011; Sendler et al. 2011; Costa et al. 2013; Conesa et al. 2016).”
BackgroundSpliceator: multi-species splice site prediction using convolutional neural networks
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“The swift improvement of highthroughput sequencing technologies for large-scale transcriptome analyses provides a means of eliminating microarray deficiencies and extending the analysis beyond the expected reference transcriptome [46].”
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Utilizing population variation, vaccination, and systems biology to study human immunology
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“Microarrays and RNA-seq are both capable technologies for obtaining transcriptomic profiles containing information on the relative level of transcripts genome-wide (note that neither provides absolute copy measures) [111–113].”
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“As demonstrated by several recent studies 45,46 , technical biases during capture and preparation of the small RNA library could impact the detection of small RNA molecules.”
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“Recently, RNA-seq has become the method of choice for in-depth analysis of the whole transcriptome of an organism (Ozsolak and Milos, 2011).”
MethodMolecular Mechanisms of Herbicide Resistance
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“Illumina short reads thus simultaneously contain transcriptome sequence information and a measure of gene expression (Ozsolak and Milos 2010).”
Reddy, N. R. R., Mehta, R. H., Soni, P. H., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0129422 · Cited by 88
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BackgroundA Review on Solar Drying Devices: Heat Transfer, Air Movement and Type of Chambers
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“variation and whole transcriptome RNA expression (1, 2).”
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Analysis of Whole Transcriptome Sequencing Data: Workflow and Software
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“The transcriptome is the entire set of RNA transcripts in a given cell for a specific developmental stage or physiological condition [1].”
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BackgroundeQTL Mapping Using RNA-seq Data
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“We refer interested readers to Ozsolak and Milos (2010) [52] and Garber et al. (2011) [21] for recent reviews of experimental and computational methods for RNA-seq, respectively.”
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“Recent major advances in DNA sequencing, ‘‘next generation sequencing (NGS)’’, provide massively parallel throughput, and data volumes that eclipse the nucleic acid information content possible with other technologies, making feasible unprecedented extensive genome analyses of groups of individuals, including analyses…”
BackgroundState of the art technologies to explore long non‐coding RNAs in cancer
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“Due to the wealth of information provided and decreased cost, the next generation sequencing (NGS) platform has gradually become one of the most common tools for studying small RNAs (15).”
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“RNA can be detected via microarrays, qPCR, 16S ribosomal RNA (rRNA) sequencing, and metatranscriptomics (Ozsolak and Milos 2011; DeAngelis et al. 2011; Geisen et al. 2015).”
BackgroundThe expression landscape of cachexia‐inducing factors in human cancers
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“We encourage readers to peruse the following recent reviews on NGS and its applications: (Boycott et al., 2013; Bras et al., 2012; Conesa et al., 2016; Davey et al., 2011; Furey, 2012; Koboldt et al., 2013; Ozsolak and Milos, 2011; Yang et al., 2015).”
InfluentialMicrofluidic Isolation of Nucleic Acids
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“Considering that detection of fusions and gene re-arrangements have high clinical relevance, it will be necessary to develop both bioinformatics methods and mate pair library construction protocols or similar technology but simpler workflows to detect re-arrangements and gene fusions (77).”
MethodThe physiology and pathobiology of human kallikrein-related peptidase 6 (KLK6)
Bayani, J., & Diamandis, E. P. (2011) · Clinical Chemistry and Laboratory Medicine (CCLM) · doi:10.1515/cclm.2011.750 · Cited by 81
Xia, C., Li, S., Hou, W., Fan, Z., Xiao, H., Lu, M., Sano, T., & Zhang, Z. (2017) · Frontiers in Microbiology · doi:10.3389/fmicb.2017.02427 · Cited by 79
“RNA-seq eliminates several of the problems associated with microarray technologies, including its restriction to known genes and limited dynamic range of detection (Ozsolak and Milos, 2011; Van Verk et al., 2013).”
BackgroundComprehensive transcriptome analysis of cochlear spiral ganglion neurons at multiple ages
Li, C., Li, X., Bi, Z., Sugino, K., Wang, G., Zhu, T., & Liu, Z. (2020) · eLife · doi:10.7554/elife.50491 · Cited by 76
CRAC: an integrated approach to the analysis of RNA-seq reads
Philippe, N., Salson, M., Commes, T., & Rivals, É. (2013) · Genome biology · doi:10.1186/gb-2013-14-3-r30 · Cited by 88
“sequencing (RNA-seq) provides genome-scale access to the RNA complement of a cell with unprecedented depth, and has therefore proven useful in unraveling the complexity of transcriptomes [1,2].”
Next-Generation Sequencing for MicroRNA Expression Profile
Hu, Y., Lan, W., & Miller, D. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-7046-9_12 · Cited by 77
Poitou, C., Perret, C., Mathieu, F., Trương, V., Blum, Y., Durand, H., Alili, R., Chelghoum, N., Pelloux, V., Aron‐Wisnewsky, J., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0125718 · Cited by 77
“Recently the RNAsequencing (RNA-seq) technology has emerged as a powerful and reliable tool for profiling gene expression which overcomes most limitations of microarrays [12].”
MethodASpli: integrative analysis of splicing landscapes through RNA-Seq assays
Mancini, E., Rabinovich, A., Iserte, J., Yanovsky, M. J., & Chernomoretz, A. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab141 · Cited by 76
Geng, R., Yuan, C., & Chen, Y. (2013) · PLoS ONE · doi:10.1371/journal.pone.0062704 · Cited by 76
Guardians of the actin monomer
Xue, B., & Robinson, R. C. (2013) · European Journal of Cell Biology · doi:10.1016/j.ejcb.2013.10.012 · Cited by 84
Individual RNA Base Recognition in Immobilized Oligonucleotides Using a Protein Nanopore
Ayub, M., & Bayley, H. (2012) · Nano Letters · doi:10.1021/nl3027873 · Cited by 76
Liao, J., Zhou, H., Peng, Q., Zhong, P.-A., Zhang, H., He, C., & Huang, Y. (2015) · BMC Genomics · doi:10.1186/s12864-015-1222-0 · Cited by 76
“The advent of next-generation high-throughput RNA sequencing technology has revolutionized transcriptome studies [23,24].”
Bai, C., Rivera, S. M., Medina, V., Alves, R., Vilaprinyó, E., Albert Sorribas, B., Canela, R., Capell, T., Sandmann, G., Christou, P., et al. (2013) · The Plant Journal · doi:10.1111/tpj.12384 · Cited by 75
The genetics and functional analysis of primary osteoarthritis susceptibility
Reynard, L. N., & Loughlin, J. A. (2013) · Expert Reviews in Molecular Medicine · doi:10.1017/erm.2013.4 · Cited by 78
Extensive cis -Regulatory Variation Robust to Environmental Perturbation in Arabidopsis
Cubillos, F. A., Stegle, O., Grondin, C., Canut, M., Tisné, S., Gy, I., & Loudet, O. (2014) · The Plant Cell · doi:10.1105/tpc.114.130310 · Cited by 73
“Moreover, studying regulatory variation using RNA-seq provides greater depth coverage per transcript than previous array-based approaches by increasing the ability to quantify and distinguish between allelic variants (McManus et al., 2010; Ozsolak and Milos, 2011).”
BackgroundTranscriptomics in Alzheimer’s Disease: Aspects and Challenges
Bagyinszky, E., Giau, V. V., & An, S. A. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21103517 · Cited by 75
Wu, Y., Wang, X., Wu, F., Huang, R., Xue, F., Liang, G., Tao, M., Cai, P., & Huang, Y. (2012) · PLoS ONE · doi:10.1371/journal.pone.0041001 · Cited by 77
“The advantage of RNA-seq is that this technique makes feasible the study of the cancer transcriptome complexity, including alternative splicing, isoform usage, gene fusions and novel transcripts (reviewed in [20,21]).”
MethodXu, H., Yao, J., Wu, D. C., & Lambowitz, A. M. (2019) · Scientific Reports · doi:10.1038/s41598-019-44457-z · Cited by 75
Cai, J., Yang, P., Zhang, C., Zhang, W., Liu, Y., Bao, Z., Liu, X., Du, W., Wang, H., Jiang, T., et al. (2014) · Oncotarget · doi:10.18632/oncotarget.1838 · Cited by 76
“In our present work, we first examined ATRX mRNA expression level using whole transcriptome sequencing, because RNA-seq can add benefits for gene expression analysis such as quantitation of transcripts, improved dynamic range, and additional capabilities for detecting expressed single nucleotide variants (SNVs), trans…”
MethodSethi, I., Romano, R., Gluck, C. B., Smalley, K., Vojtěšek, B., Buck, M. J., & Sinha, S. (2015) · BMC Genomics · doi:10.1186/s12864-015-1793-9 · Cited by 75
“Another factor that can influence the outcome of RNASeq based transcriptomic studies is the depth of sequencing coverage [46].”
BackgroundTargeted enrichment of the black cottonwood (Populus trichocarpa) gene space using sequence capture
Zhou, L., & Holliday, J. A. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-703 · Cited by 74
“Transcriptome sequencing (RNA-seq) is one option that has been available since the beginning of next-generation sequencing, and takes advantage of the natural ‘genome complexity reduction’ of the cellular transcriptional machinery [4,5].”
BackgroundUse of blood-based biomarkers for early diagnosis and surveillance of colorectal cancer
Ganepola, G. A. P. (2014) · World Journal of Gastrointestinal Oncology · doi:10.4251/wjgo.v6.i4.83 · Cited by 73
Cerveau, N., & Jackson, D. J. (2016) · BMC Bioinformatics · doi:10.1186/s12859-016-1406-x · Cited by 75
“Gene discovery, digital gene expression profiling of entire tissues or developmental stages and population genetics [1, 2] are some of the broad applications to which this technology can be applied.”
BackgroundCai, J., Zhang, W., Yang, P., Wang, Y., Li, M., Zhang, C., Wang, Z., Hu, H., Liu, Y., Li, Q., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0126022 · Cited by 73
“In our present work, mRNA expression profile of 105 primary GBM samples was examined by whole transcriptome sequencing, because RNA-seq can add benefits for gene expression analysis such as quantitation of transcripts, improved dynamic range, and additional capabilities for detecting expressed single nucleotide varian…”
BackgroundDrosophila anti-nematode and antibacterial immune regulators revealed by RNA-Seq
Castillo, J. C., Creasy, T. H., Kumari, P., Shetty, A. C., Shokal, U., Tallon, L. J., & Eleftherianos, I. (2015) · BMC Genomics · doi:10.1186/s12864-015-1690-2 · Cited by 75
“Whole genome mRNA sequencing (RNA-Seq) technologies have been a significant advance for highthroughput transcriptome analyses, as they can generate hundreds of millions reads in a single sequencing run [19, 20].”
BackgroundApplication of next generation qPCR and sequencing platforms to mRNA biomarker analysis
Devonshire, A. S., Sanders, R., Wilkes, T. M., Taylor, M. S., Foy, C. A., & Huggett, J. F. (2012) · Methods · doi:10.1016/j.ymeth.2012.07.021 · Cited by 75
Transcriptomic profiles of the bovine mammary gland during lactation and the dry period
Dai, W.-T., Zou, Y., White, R. R., Liu, J., & Liu, H. (2017) · Functional & Integrative Genomics · doi:10.1007/s10142-017-0580-x · Cited by 71
Clinical review: Sepsis and septic shock - the potential of gene arrays
Wong, H. R. (2012) · Critical Care · doi:10.1186/cc10537 · Cited by 72
“Notably, there is now an emerging technology, RNA sequencing (RNA-Seq) [6], that has potentially intriguing applications for the fi eld, but will not be further discussed as there are no RNA-Seq data specifi cally related to sepsis.”
BackgroundTranscriptome analysis of genes responding to NNV infection in Asian seabass epithelial cells
Liu, P., Wang, L., Kwang, J., Yue, G. H., & Wong, S. (2016) · Fish & Shellfish Immunology · doi:10.1016/j.fsi.2016.04.029 · Cited by 73
Wang, J., Wang, X., Sheng, N., Zhou, X., Cui, R., Zhang, H., & Dai, J. (2017) · Journal of Applied Toxicology · doi:10.1002/jat.3376 · Cited by 73
Das, A., Yang, C., Arifuzzaman, S., Kim, S., Kim, S. Y., Jung, K. H., Lee, Y. S., & Chai, Y. G. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.00022 · Cited by 71
“Thus, we performed RNA-sequencing for gene expression profiling of LPS-stimulated, IFN-γ-primed LPS-stimulated, and IL-4/IL-13-primed BMDMs, thus paving the way for an unbiased digital readout and improved detection at the extremes of the transcriptome of any mammalian cell (27).”
MethodGenetic and Molecular Basis of Feather Diversity in Birds
Ng, C. S., & Li, W. (2018) · Genome Biology and Evolution · doi:10.1093/gbe/evy180 · Cited by 73
Metadata
- Authors
- Ozsolak, F., & Milos, P. M.
- Affiliations
- Helicos Biosciences (United States) (US)
- Corresponding author
- Ozsolak, Fatih
- Milos, Patrice M.
- Venue
- Nature Reviews Genetics
- Published
- 2010-12-30
- Volume
- 12
- Issue
- 2
- Pages
- 87-98
- ISSN
- 1471-0056 (ISSN-L)
- 1471-0064
- PMC
- PMC3031867
- OpenAlex
- W2060842569
- Semantic Scholar
- cf2841f590819568ab156862c2506ab633493747
- Cited by
- 2,135
- References
- 105
- Citations by year
- 2026: 52 · 2025: 108 · 2024: 113 · 2023: 98 · 2022: 131 · 2021: 152 · 2020: 146 · 2019: 134 · 2018: 141 · 2017: 173 · 2016: 163 · 2015: 169 · 2014: 169 · 2013: 168 · 2012: 152
- FWCI
- 10.78
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Reviews Genetics (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Human Genome Research Institute (R01HG005230, R44HG005279)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Keywords
- RNA sequencing, transcriptome, direct RNA sequencing, RNA quantification, strand-specific RNA-seq, fusion gene detection, small RNA, alternative splicing
- MeSH terms
- Animals, Humans, RNA, Transcription, Genetic, Alternative Splicing, Sequence Analysis, RNA
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