The DOI matches its Crossref record; 27 of the 28 references it cites were found in a registry or an index.
RNA-sequence analysis of human B-cells
Open accessAbstract
RNA-sequencing (RNA-seq) allows quantitative measurement of expression levels of genes and their transcripts. In this study, we sequenced complementary DNA fragments of cultured human B-cells and obtained 879 million 50-bp reads comprising 44 Gb of sequence. The results allowed us to study the gene expression profile of B-cells and to determine experimental parameters for sequencing-based expression studies. We identified 20,766 genes and 67,453 of their alternatively spliced transcripts. More than 90% of the genes with multiple exons are alternatively spliced; for most genes, one isoform is predominantly expressed. We found that while chromosomes differ in gene density, the percentage of transcribed genes in each chromosome is less variable. In addition, genes involved in related biological processes are expressed at more similar levels than genes with different functions. Besides characterizing gene expression, we also used the data to investigate the effect of sequencing depth on gene expression measurements. While 100 million reads are sufficient to detect most expressed genes and transcripts, about 500 million reads are needed to measure accurately their expression levels. We provide examples in which deep sequencing is needed to determine the relative abundance of genes and their isoforms. With data from 20 individuals and about 40 million sequence reads per sample, we uncovered only 21 alternatively spliced, multi-exon genes that are not in databases; this result suggests that at this sequence coverage, we can detect most of the known genes. Results from this project are available on the UCSC Genome Browser to allow readers to study the expression and structure of genes in human B-cells.
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.
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
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849
Trapnell, C., Williams, B. A., Pertea, G., Mortazavi, A., Kwan, G., van Baren, M. J., Salzberg, S. L., Wold, B. J., & Pachter, L. (2010) · Nature Biotechnology · doi:10.1038/nbt.1621 · Cited by 15,556
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
TopHat: discovering splice junctions with RNA-Seq
Trapnell, C., Pachter, L. S., & Salzberg, S. L. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp120 · Cited by 11,682
Alternative isoform regulation in human tissue transcriptomes
Wang, E. T., Sandberg, R., Luo, S., Khrebtukova, I., Zhang, L., Mayr, C., Kingsmore, S. F., Schroth, G. P., & Burge, C. B. (2008) · Nature · doi:10.1038/nature07509 · Cited by 5,181
Pan, Q., Shai, O., Lee, L. J., Frey, B. J., & Blencowe, B. J. (2008) · Nature Genetics · doi:10.1038/ng.259 · Cited by 3,951
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
Accurate whole human genome sequencing using reversible terminator chemistry
Bentley, D. R., Balasubramanian, S., Swerdlow, H. P., Smith, G. P., Milton, J., Brown, C. G., Hall, K. P., Evers, D. J., Barnes, C. L., Bignell, H. R., et al. (2008) · Nature · doi:10.1038/nature07517 · Cited by 3,684
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
Cited by
Sorted by citations
SEQC/MAQC-III Consortium (2014) · Nature Biotechnology · doi:10.1038/nbt.2957 · Cited by 983
Bueno, R., Stawiski, E. W., Goldstein, L. D., Durinck, S., Rienzo, A. D., Modrusan, Z. D., Gnad, F., Nguyen, T. T., Jaiswal, B. S., Chirieac, L. R., et al. (2016) · Nature Genetics · doi:10.1038/ng.3520 · Cited by 937
Dual RNA-seq of pathogen and host
Westermann, A. J., Gorski, S. A., & Vogel, J. (2012) · Nature Reviews Microbiology · doi:10.1038/nrmicro2852 · Cited by 782
Calculating Sample Size Estimates for RNA Sequencing Data
Hart, S. N., Therneau, T. M., Zhang, Y., Poland, G. A., & Kocher, J.-P. (2013) · Journal of Computational Biology · doi:10.1089/cmb.2012.0283 · Cited by 341
Xu, Z., Dai, X., & Chai, X. (2018) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2018.03.348 · Cited by 327
Metadata
- Authors
- Toung, J. M., Morley, M., Li, M., & Cheung, V. G.
- Affiliations
- University of Pennsylvania (US)
- Children's Hospital of Philadelphia (US)
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2011-05-02
- Volume
- 21
- Issue
- 6
- Pages
- 991-998
- ISSN
- 1088-9051 (ISSN-L)
- PMC
- PMC3106332
- OpenAlex
- W2142108845
- Cited by
- 142
- References
- 28
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 3 · 2023: 2 · 2022: 2 · 2021: 7 · 2020: 8 · 2019: 4 · 2018: 9 · 2017: 14 · 2016: 14 · 2015: 8 · 2014: 20 · 2013: 19 · 2012: 20
- Type
- posted content
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Genome Research (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Keywords
- human B cells, gene expression profiling, alternative splicing, transcriptome, gene isoforms, sequencing depth, gene density, gene discovery, UCSC Genome Browser
- MeSH terms
- B-Lymphocytes, Humans, Proteins, Sequence Analysis, RNA, DNA, Complementary, Protein Isoforms, Gene Expression Profiling, High-Throughput Nucleotide Sequencing
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
