The DOI matches its Crossref record; 43 of the 44 references it cites were found in a registry or an index.
RNA-Seq: a revolutionary tool for transcriptomics
Open accessAbstract
RNA-Seq is a recently developed approach to transcriptome profiling that uses deep-sequencing technologies. Studies using this method have already altered our view of the extent and complexity of eukaryotic transcriptomes. RNA-Seq also provides a far more precise measurement of levels of transcripts and their isoforms than other methods. This article describes the RNA-Seq approach, the challenges associated with its application, and the advances made so far in characterizing several eukaryote transcriptomes.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“High-throughput transcriptome sequencing and digital gene expression (DGE) tag profiling are efficient and economic choice for characterizing non-model organisms without a reference genome [9], [10].”
From Digital Gene Expression Analysis Based on Integrated De Novo Transcriptome Assembly of Sweet Potato [Ipomoea batatas (L.) Lam.] (2012) · cites this paper as [10]
Experimental — accuracy not yet measuredIn the citing paper
“RNA-Seq provides comprehensive information on mRNA abundance, alternative splicing, nucleotide variation, and structure alteration.”
From Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases (2016) · cites this paper as Z. Wang et al., 2009
In the citing paper
“mNGS of RNA libraries used for the detection of pathogens such as RNA viruses in clinical samples incidentally produces host gene expression data for transcriptome (RNA-seq) analyses66.”
From Clinical metagenomics (2019) · cites this paper as [66]
In the citing paper
“Most studies have been conducted on small sample sizes and not tested on independent cohorts, or used older microarray technology, which is less accurate and reproducible than modern RNA sequencing85,86.”
From Measuring biological age using omics data (2022) · cites this paper as [85]
In the citing paper
“It should be emphasized that development of new experimental techniques such as deep-sequencing RNA-Seq,90 provides new types of data for in vitro assessment of toxicities that can also be used for QSAR modeling.91”
From QSAR without borders (2020) · cites this paper as [90]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Mapping and quantifying mammalian transcriptomes by RNA-Seq
Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696
Serial Analysis of Gene Expression
Velculescu, V. E., Zhang, L., Vogelstein, B., & Kinzler, K. W. (1995) · Science · doi:10.1126/science.270.5235.484 · Cited by 3,713
SOAP: Short oligonucleotide alignment program
Li, R., Li, Y., Kristiansen, K., & Wang, J. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn025 · Cited by 3,597
RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays
Marioni, J. C., Mason, C. E., Mane, S. M., Stephens, M., & Gilad, Y. (2008) · Genome Research · doi:10.1101/gr.079558.108 · Cited by 2,771
Mapping short DNA sequencing reads and calling variants using mapping quality scores
Li, H., Ruan, J., & Durbin, R. (2008) · Genome Research · doi:10.1101/gr.078212.108 · Cited by 2,638
The Transcriptional Landscape of the Yeast Genome Defined by RNA Sequencing
Nagalakshmi, U., Wang, Z., Waern, K., Shou, C., Raha, D., Gerstein, M., & Snyder, M. (2008) · Science · doi:10.1126/science.1158441 · Cited by 2,479
Self-citationHighly Integrated Single-Base Resolution Maps of the Epigenome in Arabidopsis
Lister, R., O’Malley, R. C., Tonti‐Filippini, J., Gregory, B. D., Berry, C. C., Millar, A. H., & Ecker, J. R. (2008) · Cell · doi:10.1016/j.cell.2008.03.029 · Cited by 2,424
Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays.
Brenner, S., Johnson, M., Bridgham, J., Golda, G., Lloyd, D. H., Johnson, D., Luo, S., McCurdy, S., Foy, M., Ewan, M., et al. (2000) · Nature Biotechnology · doi:10.1038/76469 · Cited by 1,360
TRANSLATIONAL REGULATION OFGCN4AND THE GENERAL AMINO ACID CONTROL OF YEAST
Hinnebusch, A. G. (2005) · Annual Review of Microbiology · doi:10.1146/annurev.micro.59.031805.133833 · Cited by 1,297
Sultan, M., Schulz, M. H., Richard, H., Magen, A., Klingenhoff, A., Scherf, M., Seifert, M., Borodina, T., Soldatov, A., Parkhomchuk, D., et al. (2008) · Science · doi:10.1126/science.1160342 · Cited by 1,293
Flagged first, then by citations
1 of the 44 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Items 601–700 of 1,061
Genomic insights into adaptation to high-altitude environments
Cheviron, Z. A., & Brumfield, R. T. (2011) · Heredity · doi:10.1038/hdy.2011.85 · Cited by 167
Reproductive and developmental toxicity of dioxin in fish
King‐Heiden, T. C., Mehta, V., Xiong, K. M., Lanham, K. A., Antkiewicz, D. S., Ganser, A. M., Heideman, W., & Peterson, R. E. (2011) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2011.09.027 · Cited by 167
Methods for comprehensive experimental identification of RNA-protein interactions
McHugh, C. A., Russell, P. H., & Guttman, M. (2014) · Genome biology · doi:10.1186/gb4152 · Cited by 172
Sun, K., Chen, X., Jiang, P., Song, X., Wang, H., & Sun, H. (2013) · BMC Genomics · doi:10.1186/1471-2164-14-s2-s7 · Cited by 170
Jian Xin, W. U., Zhao, Q., Yang, Q., Liu, H., Li, Q., Yi, X., Cheng, Y. F., Guo, L., Fan, C., & Zhou, Y. (2016) · Scientific Reports · doi:10.1038/srep19007 · Cited by 163
Lapehn, S., & Paquette, A. G. (2022) · Current Environmental Health Reports · doi:10.1007/s40572-022-00354-8 · Cited by 166
The core promoter: At the heart of gene expression
Danino, Y. M., Even, D. Y., Ideses, D., & Juven‐Gershon, T. (2015) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2015.04.003 · Cited by 179
The emerging CHO systems biology era: harnessing the ‘omics revolution for biotechnology
Kildegaard, H. F., Baycin-Hizal, D., Lewis, N. E., & Betenbaugh, M. J. (2013) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2013.02.007 · Cited by 165
In-depth resistome analysis by targeted metagenomics
Lanza, V. F., Baquero, F., Martínez, J. L., Ramos, R., González‐Zorn, B., Andremont, A., Valenzuela, A. S., Ehrlich, S. D., Kennedy, S., Ruppé, É., et al. (2018) · Microbiome · doi:10.1186/s40168-017-0387-y · Cited by 171
Accelerated Recruitment of New Brain Development Genes into the Human Genome
Zhang, Y. E., Landback, P., Vibranovski, M. D., & Long, M. (2011) · PLoS Biology · doi:10.1371/journal.pbio.1001179 · Cited by 164
A Genome-Wide Regulatory Framework Identifies Maize Pericarp Color1 Controlled Genes
Morohashi, K., Casas, M. I., Ferreyra, M. L. F., Mejía‐Guerra, M. K., Pourcel, L., Yılmaz, A., Feller, A., Carvalho, B., Emiliani, J., Rodrı́guez, E., et al. (2012) · The Plant Cell · doi:10.1105/tpc.112.098004 · Cited by 164
Beaulieu, Y. B., Kleinman, C. L., Landry-Voyer, A.-M., Majewski, J., & Bachand, F. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1003078 · Cited by 167
Next-Generation Sequencing Accelerates Crop Gene Discovery
Nguyen, K., Grondin, A., Courtois, B., & Gantet, P. (2018) · Trends in Plant Science · doi:10.1016/j.tplants.2018.11.008 · Cited by 167
Sekhon, R. S., Briskine, R., Hirsch, C. N., Myers, C. L., Springer, N. M., Buell, C. R., de Leon, N., & Kaeppler, S. M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061005 · Cited by 163
Single Nucleotide Polymorphism Identification in Polyploids: A Review, Example, and Recommendations
Clevenger, J. P., Chavarro, C. M., Pearl, S. A., Ozias‐Akins, P., & Jackson, S. A. (2015) · Molecular Plant · doi:10.1016/j.molp.2015.02.002 · Cited by 175
Bias detection and correction in RNA-Sequencing data
Zheng, W., Chung, L. M., & Zhao, H. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-290 · Cited by 169
RNA Biomarkers: Frontier of Precision Medicine for Cancer
Xi, X., Li, T., Huang, Y., Sun, J., Zhu, Y., Yang, Y., & Lu, Z. J. (2017) · Non-Coding RNA · doi:10.3390/ncrna3010009 · Cited by 163
Graf, A., Krebs, S., Heininen-Brown, M., Zakhartchenko, V., Blum, H., & Wolf, E. (2014) · Animal Reproduction Science · doi:10.1016/j.anireprosci.2014.05.016 · Cited by 175
Impacts of Variation in the Human Genome on Gene Regulation
Haraksingh, R., & Snyder, M. P. (2013) · Journal of Molecular Biology · doi:10.1016/j.jmb.2013.07.015 · Cited by 169
Self-citationBashir, K., Matsui, A., Rasheed, S., & Seki, M. (2019) · F1000Research · doi:10.12688/f1000research.18424.1 · Cited by 163
Asmann, Y. W., Klee, E. W., Thompson, E. A., Perez, E. A., Middha, S., Oberg, A. L., Therneau, T. M., Smith, D. I., Poland, G. A., Wieben, E. D., et al. (2009) · BMC Genomics · doi:10.1186/1471-2164-10-531 · Cited by 167
Next-generation sequencing technologies for gene expression profiling in plants
Jain, M. (2011) · Briefings in Functional Genomics · doi:10.1093/bfgp/elr038 · Cited by 166
Wang, H., Zhang, Y., Wang, T., Yang, Q., Yang, Y., Li, Z., Li, B., Wen, X., Yin, W., Yin, W., et al. (2021) · The Plant Cell · doi:10.1093/plcell/koab046 · Cited by 163
Ribosomal RNA Depletion for Efficient Use of RNA‐Seq Capacity
O’Neil, D., Glowatz, H., & Schlumpberger, M. (2013) · Current Protocols in Molecular Biology · doi:10.1002/0471142727.mb0419s103 · Cited by 154
Epigenetic Control of Gene Expression in the Lung
Yang, I. V., & Schwartz, D. A. (2011) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201010-1579pp · Cited by 169
Liu, G., Li, W., Zheng, P., Xu, T., Chen, L., Liu, D., Hussain, S., & Teng, Y. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-700 · Cited by 159
ReCount: A multi-experiment resource of analysis-ready RNA-seq gene count datasets
Frazee, A. C., Langmead, B., & Leek, J. T. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-449 · Cited by 157
Misquitta-Ali, C. M., Cheng, E., O’Hanlon, D., Liu, G., McGlade, C. J., Tsao, M., & Blencowe, B. J. (2010) · Molecular and Cellular Biology · doi:10.1128/mcb.00709-10 · Cited by 162
Model-based clustering for RNA-seq data
Si, Y., Liu, P., Li, P., & Brutnell, T. P. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt632 · Cited by 161
High levels of RNA-editing site conservation amongst 15 laboratory mouse strains
Danecek, P., Nellåker, C., McIntyre, R. E., Buendia-Buendia, J. E., Bumpstead, S., Ponting, C. P., Flint, J., Durbin, R. M., Keane, T., & Adams, D. J. (2012) · Genome biology · doi:10.1186/gb-2012-13-4-r26 · Cited by 159
Emerging Targeted Therapy for Tumors with NTRK Fusion Proteins
Kheder, E., & Hong, D. S. (2018) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-18-1156 · Cited by 163
Function and Evolution of Upstream ORFs in Eukaryotes
Zhang, H., Wang, Y., & Lü, J. (2019) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2019.03.002 · Cited by 160
Huang, J., Jiang, E., Yang, D., Wei, J., Zhao, M., Feng, J., & Cao, J. (2020) · Infection and Drug Resistance · doi:10.2147/idr.s235182 · Cited by 161
Evolutionary history and stress regulation of the lectin superfamily in higher plants
Jiang, S., Ma, Z., & Ramachandran, S. (2010) · BMC Evolutionary Biology · doi:10.1186/1471-2148-10-79 · Cited by 167
FusionSeq: a modular framework for finding gene fusions by analyzing paired-end RNA-sequencing data
Sboner, A., Habegger, L., Pflueger, D., Terry, S., Chen, D. Z., Rozowsky, J. S., Tewari, A. K., Kitabayashi, N., Moss, B. J., Chee, M. S., et al. (2010) · Genome biology · doi:10.1186/gb-2010-11-10-r104 · Cited by 158
Self-citationConservation Genomics of Threatened Animal Species
Steiner, C., Putnam, A. S., Hoeck, P. E. A., & Ryder, O. A. (2013) · Annual Review of Animal Biosciences · doi:10.1146/annurev-animal-031412-103636 · Cited by 169
RNA-seq and microarray complement each other in transcriptome profiling
Kogenaru, S., Yan, Q., Guo, Y., & Wang, N. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-629 · Cited by 157
Control of seed dormancy in Arabidopsis by a cis -acting noncoding antisense transcript
Fedak, H., Palusińska, M., Krzyczmonik, K., Brzezniak, L. K., Yatusevich, R., Pietras, Z., Kaczanowski, S., & Świeżewski, S. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1608827113 · Cited by 159
Gene Networks Underlying Cannabinoid and Terpenoid Accumulation in Cannabis
Zager, J. J., Lange, I., Srividya, N., Smith, A., & Lange, B. M. (2019) · PLANT PHYSIOLOGY · doi:10.1104/pp.18.01506 · Cited by 164
Milk microbiota: Characterization methods and role in cheese production
Tilocca, B., Costanzo, N., Morittu, V. M., Spina, A. A., Soggiù, A., Britti, D., Roncada, P., & Piras, C. (2019) · Journal of Proteomics · doi:10.1016/j.jprot.2019.103534 · Cited by 171
Khan, I. M., Cao, Z., Liu, H., Khan, A. A., Rahman, S. U., Khan, M. Z., Sathanawongs, A., & Zhang, Y. (2021) · Frontiers in Veterinary Science · doi:10.3389/fvets.2021.609180 · Cited by 159
IVT-seq reveals extreme bias in RNA sequencing
Lahens, N. F., Kavakli, I. H., Zhang, R., Hayer, K., Black, M. B., Dueck, H., Pizarro, A., Kim, J., Irizarry, R., Thomas, R. S., et al. (2014) · Genome Biology · doi:10.1186/gb-2014-15-6-r86 · Cited by 158
RNA interference: Applications and advances in insect toxicology and insect pest management
Kim, Y. H., Issa, M. S., Cooper, A. M. W., & Zhu, K. Y. (2015) · Pesticide Biochemistry and Physiology · doi:10.1016/j.pestbp.2015.01.002 · Cited by 158
Systematic identification of genes with a cancer-testis expression pattern in 19 cancer types
Wang, C., Gu, Y., Zhang, K., Xie, K., Zhu, M., Dai, N., Jiang, Y., Guo, X., Liu, M., Dai, J., et al. (2016) · Nature Communications · doi:10.1038/ncomms10499 · Cited by 161
Transcriptomic responses in the fish intestine
Martín, S., Dehler, C. E., & Król, E. (2016) · Developmental & Comparative Immunology · doi:10.1016/j.dci.2016.03.014 · Cited by 157
Computational approaches to disease‐gene prediction: rationale, classification and successes
Piro, R. M., & Cunto, F. D. (2012) · FEBS Journal · doi:10.1111/j.1742-4658.2012.08471.x · Cited by 156
Meyer, U. A., Zanger, U. M., & Schwab, M. (2013) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-010510-100502 · Cited by 157
Challenges of sequencing human genomes
Koboldt, D. C., Ding, L., Mardis, E. R., & Wilson, R. K. (2010) · Briefings in Bioinformatics · doi:10.1093/bib/bbq016 · Cited by 161
Spatial transcriptomics: paving the way for tissue-level systems biology
Moor, A. E., & Itzkovitz, S. (2017) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2017.02.004 · Cited by 155
Next‐generation biological control: the need for integrating genetics and genomics
Leung, K., Ras, E., Ferguson, K., Ariëns, S., Babendreier, D., Bijma, P., Bourtzis, K., Jacques Brodeur, B., Bruins, M. A., Centurión, A., et al. (2020) · Biological reviews/Biological reviews of the Cambridge Philosophical Society · doi:10.1111/brv.12641 · Cited by 157
Current Achievements and Applications of Transcriptomics in Personalized Cancer Medicine
Supplitt, S., Karpiński, P., Sasiadek, M. M., & Łaczmańska, I. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22031422 · Cited by 166
Heimberg, G., Bhatnagar, R., El-Samad, H., & Thomson, M. (2016) · Cell Systems · doi:10.1016/j.cels.2016.04.001 · Cited by 156
Genetics of the polycystic ovary syndrome
Kosova, G., & Urbanek, M. (2013) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2012.10.009 · Cited by 156
DiffSplice: the genome-wide detection of differential splicing events with RNA-seq
Hu, Y., Huang, Y., Du, Y., Orellana, C. F., Singh, D., Johnson, A., Monroy‐Eklund, A., Kuan, P. F., Hammond, S. M., Makowski, L., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1026 · Cited by 164
Zhou, Y., Yang, P., Cui, F., Zhang, F., Luo, X., & Xie, J. (2016) · PLoS ONE · doi:10.1371/journal.pone.0146242 · Cited by 155
NPInter v3.0: an upgraded database of noncoding RNA-associated interactions
Hao, Y., Wu, W., Li, H., Yuan, J., Luo, J., Zhao, Y. C., & Chen, R. (2016) · Database · doi:10.1093/database/baw057 · Cited by 162
Gene Regulatory Network Inference: An Introductory Survey
Huynh‐Thu, V. A., & Sanguinetti, G. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-8882-2_1 · Cited by 163
Franssen, S. U., Shrestha, R. P., Bräutigam, A., Bornberg‐Bauer, E., & Weber, A. P. M. (2011) · BMC Genomics · doi:10.1186/1471-2164-12-227 · Cited by 158
RNA-Seq: revelation of the messengers
Verk, M. C. V., Hickman, R. J., Pieterse, C. M. J., & Wees, S. C. M. V. (2013) · Trends in Plant Science · doi:10.1016/j.tplants.2013.02.001 · Cited by 156
Temperate pasture legumes in Australia—their history, current use, and future prospects
Nichols, P. G. H., Revell, C. K., Humphries, A. W., Howie, J., Hall, E. J., Sandral, G. A., Ghamkhar, K., & Harris, C. A. (2012) · Australian Journal of Agricultural Research · doi:10.1071/cp12194 · Cited by 155
Maza, É. (2016) · Frontiers in Genetics · doi:10.3389/fgene.2016.00164 · Cited by 153
microRNAs and genetic diseases
Meola, N., Gennarino, V. A., & Banfi, S. (2009) · PathoGenetics · doi:10.1186/1755-8417-2-7 · Cited by 158
Tuch, B. B., Mitrovich, Q. M., Homann, O. R., Hernday, A. D., Monighetti, C. K., Vega, F. M. D. L., & Johnson, A. D. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1001070 · Cited by 152
Cytological, physiological, and transcriptomic analyses of golden leaf coloration in Ginkgo biloba L
Li, W., Yang, S., Lu, Z., He, Z., Ye, Y., Zhao, B., Wang, L., & Jin, B. (2018) · Horticulture Research · doi:10.1038/s41438-018-0015-4 · Cited by 154
Molecular subtyping of cancer: current status and moving toward clinical applications
Zhao, L., Lee, V. H.-F., Ng, M. K., Yan, H., & Bijlsma, M. F. (2018) · Briefings in Bioinformatics · doi:10.1093/bib/bby026 · Cited by 156
Evolving Strategies for Target Selection for Antibody-Drug Conjugates
Damelin, M. I., Zhong, W., Myers, J. S., & Sapra, P. (2015) · Pharmaceutical Research · doi:10.1007/s11095-015-1624-3 · Cited by 155
Chen, T., Lv, Y., Zhao, T., Li, N., Yang, Y., Yu, W., He, X., Liu, T., & Zhang, B. (2013) · PLoS ONE · doi:10.1371/journal.pone.0080816 · Cited by 153
Park, S. H., Aydın, M., Khatiwara, A., Dolan, M. C., Gilmore, D. F., Bouldin, J. L., Ahn, S., & Ricke, S. C. (2013) · Food Microbiology · doi:10.1016/j.fm.2013.10.002 · Cited by 153
Genome-scale transcriptome analysis of the desert poplar, Populus euphratica
Qiu, Q., Ma, T., Hu, Q., Liu, B., Wu, Y., Zhou, H., Wang, L., Wang, J., & Liu, J. (2011) · Tree Physiology · doi:10.1093/treephys/tpr015 · Cited by 152
Transcriptome analysis of rice root heterosis by RNA-Seq
Zhai, R., Feng, Y., Wang, H., Zhan, X., Shen, X., Wu, W., Zhang, Y., Chen, D., Dai, G., Yang, Z.-L., et al. (2013) · BMC Genomics · doi:10.1186/1471-2164-14-19 · Cited by 153
Hamfjord, J., Stangeland, A. M., Hughes, T., Skrede, M. L., Tveit, K. M., Ikdahl, T., & Kure, E. H. (2012) · PLoS ONE · doi:10.1371/journal.pone.0034150 · Cited by 153
A comprehensive assessment of RNA-seq protocols for degraded and low-quantity samples
Schuierer, S., Carbone, W., Knehr, J., Petitjean, V., Fernandez, A., Sultan, M., & Roma, G. (2017) · BMC Genomics · doi:10.1186/s12864-017-3827-y · Cited by 149
Serum, plasma and saliva biomarkers for head and neck cancer
Arantes, L. M. R. B., de Carvalho, A. C., Melendez, M. E., & Carvalho, A. L. (2017) · Expert Review of Molecular Diagnostics · doi:10.1080/14737159.2017.1404906 · Cited by 153
Plant Thaumatin-like Proteins: Function, Evolution and Biotechnological Applications
Pires, C. D. J., Ferreira‐Neto, J. R. C., Bezerra-Neto, J. P., Kido, É. A., Silva, R. L. D. O., Pandolfi, V., Wanderley-Nogueira, A. C., Binneck, E., da Costa, A. F., Pio‐Ribeiro, G., et al. (2019) · Current Protein and Peptide Science · doi:10.2174/1389203720666190318164905 · Cited by 153
The next-generation sequencing technology and application
Zhou, X., Ren, L., Meng, Q., Li, Y., Yu, Y., & Yu, J. M. (2010) · Protein & Cell · doi:10.1007/s13238-010-0065-3 · Cited by 161
Getting Started in Gene Expression Microarray Analysis
Slonim, D. K., & Yanai, I. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000543 · Cited by 155
Assessing the impact of transcriptomics, proteomics and metabolomics on fungal phytopathology
Tan, K., IPCHO, S. V. S., Trengove, R. D., Oliver, R. P., & Solomon, P. S. (2009) · Molecular Plant Pathology · doi:10.1111/j.1364-3703.2009.00565.x · Cited by 152
An efficient method for long-term room temperature storage of RNA
Fabre, A.-L., Colotte, M., Luis, A., Tuffet, S., & Bonnet, J. (2014) · European Journal of Human Genetics · doi:10.1038/ejhg.2013.145 · Cited by 151
Ranjan, A., Ichihashi, Y., Farhi, M., Zumstein, K., Townsley, B. T., David‐Schwartz, R., & Sinha, N. R. (2014) · PLANT PHYSIOLOGY · doi:10.1104/pp.113.234864 · Cited by 151
Huang, G., Wu, X., Shi, L., Xu, X., Hua, Z., & Chen, X. (2016) · Scientific Reports · doi:10.1038/srep26524 · Cited by 153
Zouine, M., Maza, É., Djari, A., Lauvernier, M., Frasse, P., Smouni, A., Pirrello, J., & Bouzayen, M. (2017) · The Plant Journal · doi:10.1111/tpj.13711 · Cited by 151
Plant MetGenMAP: An Integrative Analysis System for Plant Systems Biology
Joung, J., Corbett, A. M., Moore, S. L., Tieman, D. M., Klee, H. J., Giovannoni, J. J., & Fei, Z. (2009) · PLANT PHYSIOLOGY · doi:10.1104/pp.109.145169 · Cited by 150
Porichis, F., Hart, M. G., Griesbeck, M., Everett, H. L., Hassan, M., Baxter, A. E., Lindqvist, M., Miller, S. M., Soghoian, D. Z., Kavanagh, D. G., et al. (2014) · Nature Communications · doi:10.1038/ncomms6641 · Cited by 150
Himes, B. E., Jiang, X., Wagner, P., Hu, R., Wang, Q., Klanderman, B. J., Whitaker, R. M., Duan, Q., Lasky-Su, J. A., Nikolos, C., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0099625 · Cited by 152
Gao, J., Sun, L. V., Yang, X., & Liu, J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0064643 · Cited by 150
De Novo Transcriptome Sequencing in Anopheles funestus Using Illumina RNA-Seq Technology
Crawford, J. E., Guelbeogo, M. W., Sanou, A., Traoré, A., Vernick, K. D., Sagnon, N., & Lazzaro, B. P. (2010) · PLoS ONE · doi:10.1371/journal.pone.0014202 · Cited by 153
Bunnik, E. M., Chung, D.-W. D., Hamilton, M., Ponts, N., Saraf, A., Prudhomme, J. G., Florens, L. A., & Roch, K. G. L. (2013) · Genome biology · doi:10.1186/gb-2013-14-11-r128 · Cited by 146
RBFox1-mediated RNA splicing regulates cardiac hypertrophy and heart failure
Gao, C., Ren, S. V., Lee, J., Qiu, J., Chapski, D. J., Rau, C. D., Zhou, Y., Abdellatif, M., Nakano, A., Vondriska, T. M., et al. (2015) · Journal of Clinical Investigation · doi:10.1172/jci84015 · Cited by 150
Sexual plasticity: A fishy tale
Liu, H., Todd, E. V., Lokman, P. M., Lamm, M. S., Godwin, J., & Gemmell, N. J. (2016) · Molecular Reproduction and Development · doi:10.1002/mrd.22691 · Cited by 150
Transcriptional recording by CRISPR spacer acquisition from RNA
Schmidt, F., Cherepkova, M. Y., & Platt, R. J. (2018) · Nature · doi:10.1038/s41586-018-0569-1 · Cited by 149
Transcriptomics in aquaculture: current status and applications
Chandhini, S., & Rejish Kumar, V. J. (2018) · Reviews in Aquaculture · doi:10.1111/raq.12298 · Cited by 150
Mutation Mechanism of Leaf Color in Plants: A Review
Zhao, M., Li, X., Zhang, X.-X., Zhang, H., & Zhao, X. (2020) · Forests · doi:10.3390/f11080851 · Cited by 150
The ENCODE Uniform Analysis PipelinesPreprint
Hitz, B. C., Lee, J.-W., Jolanki, O., Kagda, M. S., Graham, K., Sud, P., Gabdank, I., Strattan, J. S., Sloan, C. A., Dreszer, T. R., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.04.535623 · Cited by 149
High-throughput profiling of influenza A virus hemagglutinin gene at single-nucleotide resolution
Wu, N. C., Young, A. P., Al‐Mawsawi, L. Q., Olson, C. A., Feng, J., Qi, H., Chen, S., Lu, I.-H., Lin, C., Chin, R. G., et al. (2014) · Scientific Reports · doi:10.1038/srep04942 · Cited by 151
Specialized phenolic compounds in seeds: structures, functions, and regulations
Corso, M., Perreau, F., Mouille, G., & Lepiniec, L. (2020) · Plant Science · doi:10.1016/j.plantsci.2020.110471 · Cited by 158
Lawson, N. D., Li, R., Shin, M., Grosse, A. S., Yukselen, O., Stone, O. A., Küçükural, A., & Zhu, L. J. (2020) · eLife · doi:10.7554/elife.55792 · Cited by 155
Evans, T. G. (2015) · Journal of Experimental Biology · doi:10.1242/jeb.114306 · Cited by 152
Systems biology of asthma and allergic diseases: A multiscale approach
Bunyavanich, S., & Schadt, E. E. (2014) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2014.10.015 · Cited by 149
Bell, G. D. M., Kane, N. C., Rieseberg, L. H., & Adams, K. L. (2013) · Genome Biology and Evolution · doi:10.1093/gbe/evt072 · Cited by 142
RNA-Seq and molecular docking reveal multi-level pesticide resistance in the bed bug
Mamidala, P., Wijeratne, A., Wijeratne, S., Kornacker, K., Sudhamalla, B., Rivera-Vega, L. J., Hoelmer, A., Meulia, T., Jones, S. C., & Mittapalli, O. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-6 · Cited by 148
Metadata
- Authors
- Wang, Z., Gerstein, M., & Snyder, M.
- Affiliations
- Yale University (US)
- Corresponding author
- Snyder, Michael
- Venue
- Nature Reviews Genetics
- Published
- 2009-01
- Volume
- 10
- Issue
- 1
- Pages
- 57-63
- ISSN
- 1471-0056 (ISSN-L)
- 1471-0064
- PMC
- PMC2949280
- OpenAlex
- W1981509058
- Cited by
- 13,174
- References
- 44
- Citations by year
- 2026: 518 · 2025: 745 · 2024: 728 · 2023: 662 · 2022: 856 · 2021: 974 · 2020: 916 · 2019: 862 · 2018: 911 · 2017: 867 · 2016: 901 · 2015: 960 · 2014: 900 · 2013: 815 · 2012: 662
- FWCI
- 22.07
- 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 (P50HG002357)
- National Cancer Institute (R01CA077808)
- 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-seq, transcriptomics, gene expression profiling, deep sequencing, mRNA isoforms, transcript quantification, next-generation sequencing
- MeSH terms
- Animals, Base Sequence, Chromosome Mapping, Exons, Humans, Models, Genetic, Molecular Sequence Data, RNA, Transcription, Genetic, Sequence Analysis, RNA, Gene Expression Profiling
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
