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An Atlas of Human Gene Expression from Massively Parallel Signature Sequencing (MPSS)

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An Atlas of Human Gene Expression from Massively Parallel Signature Sequencing (MPSS) Downloaded from genome.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press Resource An atlas of human gene expression from massively parallel signature sequencing (MPSS) C. Victor Jongeneel,1,6 Mauro Delorenzi,2 Christian Iseli,1 Daixing Zhou,4 Christian D. Haudenschild,4 Irina Khrebtukova,4 Dmitry Kuznetsov,1 Brian J. Stevenson,1 Robert L. Strausberg,5 Andrew J.G. Simpson,3 and Thomas J. Vasicek4 1Office of Information Technology, Ludwig Institute for Cancer Research, and Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; 2National Center for Competence in Research in Molecular Oncology, Swiss Institute for Experimental Cancer Research (ISREC) and Swiss Institute of Bioinformatics, 1066 Epalinges, Switzerland; 3Ludwig Institute for Cancer Research, New York, New York 10012, USA; 4Solexa, Inc., Hayward, California 94545, USA; 5The J. Craig Venter Institute, Rockville, Maryland 20850, USA We have used massively parallel signature sequencing (MPSS) to sample the transcriptomes of 32 normal human tissues to an unprecedented depth, thus documenting the patterns of expression of almost 20,000 genes with high sensitivity and specificity. The data confirm the widely held belief that differences in gene expression between cell and tissue types are largely determined by transcripts derived from a limited number of tissue-specific genes, rather than by combinations of more promiscuously expressed genes. Expression of a little more than half of all known human genes seems to account for both the common requirements and the specific functions of the tissues sampled. A classification of tissues based on patterns of gene expression largely reproduces classifications based on anatomical and biochemical properties. The unbiased sampling of the human transcriptome achieved by MPSS supports the idea that most human genes have been mapped, if not functionally characterized. This data set should prove useful for the identification of tissue-specific genes, for the study of global changes induced by pathological conditions, and for the definition of a minimal set of genes necessary for basic cell maintenance. The data are available on the Web at http://mpss.licr.org and http://sgb.lynxgen.com. [Supplemental material is available online at www.genome.org. The following individuals kindly provided reagents, samples, or unpublished information as indicated in the paper: A. Delaney.] As a rule, adult human organs and tissues perform highly spe- levels of these genes give valuable insights into the specialized cialized tasks, and contain cell types that have gone through an functions performed by fully differentiated tissues, and into the extensive differentiation program. Cells belonging to different gene products required to maintain them. Moreover, these data tissues can be distinguished morphologically, functionally, and largely define the complement of genes expressed in a variety of biochemically. Differentiation is driven largely by changes in the normal tissues, and thus a backdrop against which pathological transcriptional program of the cells, through regulatory and epi- changes can be detected and analyzed. genetic events. Therefore, the availability of comprehensive snapshots of the transcriptomes of cell populations from fully differentiated tissues should give us valuable information about Results the genes whose expression is necessary to maintain their spe- Depth of coverage and mapping of signatures cialized functions, as well as those that are necessary to all living cells. We have shown previously that massively parallel signature mRNA populations extracted from 23 different non-CNS organs sequencing (MPSS) is a technique that can provide such a picture, and from nine different CNS areas (Table 1) were subjected to 106 ן to 6 106 ן at least for the vast majority of human transcripts (Jongeneel et MPSS analysis (Brenner et al. 2000a), with 1.3 al. 2003). MPSS is unlike microarrays, where issues of array de- signatures being generated in two reading phases for each sign, cross-hybridization and reproducibility limit the coverage sample. The cDNA libraries attached to microbeads were pro- and dynamic range of the assay. MPSS also has the advantage duced using the original Megaclone protocol (Brenner et al. that it samples the transcripts present in an mRNA population in 2000b), which includes the amplification by PCR of the entire an essentially unbiased fashion. region between the poly(A) tail and the first DpnII site on the We have analyzed pooled RNA samples isolated from 32 cDNA. Six batches of loaded beads were used for sequencing each molecules 105 ן human tissues, and were able to document the patterns of ex- sample, each representing an aliquot of 1.6 to 107 ן pression of 18,667 genes. The identities and relative expression drawn from an initial library with a complexity of 4 independent cDNA/vector ligations; therefore, the 108 ן 4 6 .105 ן Corresponding author. maximum complexity of the sampled population is 9.6 E-mail [email protected]; fax 41-21-6924065. Article and publication are at http://www.genome.org/cgi/doi/10.1101/ Only signatures seen in at least two independent sequencing gr.4041005. runs and present at a minimum number of three transcripts per 15:1007–1014 ©2005 by Cold Spring Harbor Laboratory Press; ISSN 1088-9051/05; www.genome.org Genome Research 1007 www.genome.org Downloaded from genome.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press Jongeneel et al. Table 1. Tissues sampled and annotation process Tissue Clones Signatures Mapped % mapped Genes In loci Reverse Genome Unmapped Adrenal gland 3.4 28,610 17,352 60.7% 9761 7166 3403 434 255 Bladder 2.5 25,795 14,092 54.6% 8284 6787 4320 480 116 Bone marrow 2.5 21,392 11,352 53.1% 7182 5492 3592 264 692 Brain (amygdala) 3.1 30,777 17,886 58.1% 10,168 8370 3594 693 234 Brain (caudate nucleus) 3.0 28,749 16,940 58.9% 9948 7509 3446 646 208 Brain (cerebellum) 1.8 27,372 13,413 49.0% 8183 9152 3880 717 210 Brain (corpus callosum) 3.5 31,526 18,302 58.1% 10,210 8679 3632 656 257 Brain (fetal) 4.7 27,030 13,699 50.7% 8447 9110 3158 765 298 Brain (hypothalamus) 2.2 27,474 16,710 60.8% 9867 6371 3384 585 424 Brain (thalamus) 1.5 25,936 15,680 60.5% 9389 6719 2800 551 186 Heart 3.6 27,335 16,906 61.8% 9379 5689 4147 369 224 Kidney 2.5 20,996 12,366 58.9% 7631 4425 3647 368 190 Lung 3.2 29,071 17,344 59.7% 9836 7384 3713 381 249 Mammary gland 2.6 20,014 13,162 65.8% 8351 4378 1979 321 174 Pancreas 2.4 11,634 8280 71.2% 5845 1958 1192 113 91 Pituitary gland 2.2 25,997 15,381 59.2% 9220 6255 3568 591 202 Placenta 5.3 16,344 10,236 62.6% 6631 3790 1856 283 179 Prostate 3.2 21,097 12,521 59.3% 7941 5427 2584 338 227 Retina 4.3 27,152 16,504 60.8% 9891 6368 3380 537 363 Salivary gland 3.6 17,598 11,706 66.5% 7540 4065 1476 223 128 Small intestine 5.0 29,599 18,084 61.1% 10,286 7902 2898 485 230 Spinal cord 4.2 30,367 18,920 62.3% 10,632 7214 3437 585 211 Spleen 3.1 34,956 19,988 57.2% 10,594 9877 4198 579 314 Stomach 3.1 13,992 9544 68.2% 6537 2995 1205 161 87 Testis 3.4 39,127 22,731 58.1% 12,267 9549 4944 1490 413 Thymus 5.5 36,250 19,871 54.8% 10,470 11,215 4001 742 421 Thyroid 6.0 29,210 17,596 60.2% 9870 7190 3556 487 381 Trachea 3.0 27,516 17,823 64.8% 10,201 6620 2333 440 300 Uterus 4.9 34,187 20,085 58.8% 10,737 9528 3753 529 292 Colon 1.3 13,982 9293 66.5% 6149 3267 1090 238 94 Monocytes 1.9 22,351 13,674 61.2% 7533 5125 2764 436 352 Peripheral blood lymphocytes 2.0 17,844 11,910 66.7% 7202 4407 1147 264 116 Total 104.6 142,872 48,339 33.8% 18,677 53,402 29,661 7200 4270 The column labels are clones: the number of clones (in millions) sequenced for this tissue; signatures: the number of different significant signatures observed in the tissue, excluding those mapping to contaminants (ribosomal, mitochondrial, repetitive elements), those mapping to more than four genes, and those mapping with single nucleotide mismatches; mapped: the number of signatures reliably mapped to transcripts (plus strand of known exons); % mapped: the percentage of signatures that were reliably mapped; genes: the number of transcribed regions to which the reliable signatures map; in loci: the number of signatures that map within loci, but to regions not known to be transcribed (in introns or within 5 kb downstream of polyadenylation site); reverse: the number of signatures that map to the reverse strand of known transcripts; genome: the number of signatures that map to the human genome outside of known loci; unmapped: the number of signatures that do not map to the human genome. Note that some categories of signatures, for example, those derived from noncoding RNAs or mapped with single nucleotide mismatches, are not represented in this table; these were excluded from the calculated percentages. million (tpm) in at least one sample were retained. This proce- tissue-specific. The details of the mapping process are summa- dure ensures that most signatures containing sequencing errors rized in Table 1. are removed (Meyers et al. 2004). A total of 182,718 distinct The signatures that could not be assigned to known tran- signatures fulfilled these criteria.
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