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Comparing whole genomes using DNA microarrays

Key Points

  • Hybridization between complementary strands of DNA enables the interrogation of unknown DNA by comparison with DNA of known sequence or genomic context.

  • DNA microarrays containing hundreds of thousands or millions of probes can be used to interrogate genomic sequence. Advances in array-based approaches have enabled detection of the main forms of genomic variation: amplifications, deletions, insertions, rearrangements and base-pair changes.

  • Structural variation in the genome — deletions and duplications, copy number variation, insertions, inversions and chromosomal translocations — can be detected using array comparative genome hybridization. For this application it is often sufficient to have large probes (such as PCR products, cDNA clones or long oligonucleotides) that allow for hybridization despite some sequence differences.

  • When DNA probes are short, hybridization efficiency is acutely sensitive to mismatches; such probes therefore facilitate comparison of genomes at the nucleotide level.

  • Global mapping of insertion sites is performed by isolating the insertion element and its immediately neighbouring DNA. The DNA is then hybridized to a whole-genome array to identify its genomic location.

  • Comprehensive detection of mutations in a complex genome is carried out using whole-genome overlapping tiling arrays, which provide multiple measurements of the effect of an SNP on hybridization.

  • Resequencing arrays use at least four probes per interrogated base and have been used to resequence small genomes.

  • Microarrays offer a relatively inexpensive and efficient means of comparing all known classes of genomic diversity between closely related genomes. However, they are not appropriate for some applications, such as detecting unknown sequences or interrogating highly repetitive or low-complexity sequences.

Abstract

The rapid accumulation of complete genomic sequences offers the opportunity to carry out an analysis of inter- and intra-individual genome variation within a species on a routine basis. Sequencing whole genomes requires resources that are currently beyond those of a single laboratory and therefore it is not a practical approach for resequencing hundreds of individual genomes. DNA microarrays present an alternative way to study differences between closely related genomes. Advances in microarray-based approaches have enabled the main forms of genomic variation (amplifications, deletions, insertions, rearrangements and base-pair changes) to be detected using techniques that are readily performed in individual laboratories using simple experimental approaches.

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Figure 1: Identifying copy number variation in genomes using array comparative genome hybridization.
Figure 2: Detecting SNP variation using microarrays.
Figure 3: Genome-wide mapping of loci by selective enrichment and detection using microarrays.

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References

  1. Sanger, F., Nicklen, S. & Coulson, A. R. DNA sequencing with chain-terminating inhibitors. Proc. Natl Acad. Sci. USA 74, 5463–5467 (1977).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Sanger, F. et al. Nucleotide sequence of bacteriophage φX174 DNA. Nature 265, 687–695 (1977).

    Article  CAS  PubMed  Google Scholar 

  3. Lander, E. S. et al. Initial sequencing and analysis of the human genome. Nature 409, 860–921 (2001).

    Article  CAS  PubMed  Google Scholar 

  4. Venter, J. C. et al. The sequence of the human genome. Science 291, 1304–1351 (2001).

    Article  CAS  PubMed  Google Scholar 

  5. Venter, J. C., Levy, S., Stockwell, T., Remington, K. & Halpern, A. Massive parallelism, randomness and genomic advances. Nature Genet. 33, 219–227 (2003).

    Article  CAS  PubMed  Google Scholar 

  6. DeRisi, J. L., Iyer, V. R. & Brown, P. O. Exploring the metabolic and genetic control of gene expression on a genomic scale. Science 278, 680–686 (1997).

    Article  CAS  PubMed  Google Scholar 

  7. Velculescu, V. E. et al. Characterization of the yeast transcriptome. Cell 88, 243–251 (1997).

    Article  CAS  PubMed  Google Scholar 

  8. Winzeler, E. A. et al. Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. Science 285, 901–906 (1999).

    Article  CAS  PubMed  Google Scholar 

  9. Kamath, R. S. et al. Systematic functional analysis of the Caenorhabditis elegans genome using RNAi. Nature 421, 231–237 (2003).

    Article  CAS  PubMed  Google Scholar 

  10. Ghaemmaghami, S. et al. Global analysis of protein expression in yeast. Nature 425, 737–741 (2003).

    Article  CAS  PubMed  Google Scholar 

  11. Reboul, J. et al. C. elegans ORFeome version 1.1: experimental verification of the genome annotation and resource for proteome-scale protein expression. Nature Genet. 34, 35–41 (2003).

    Article  PubMed  Google Scholar 

  12. Shendure, J. et al. Accurate multiplex polony sequencing of an evolved bacterial genome. Science 309, 1728–1732 (2005).

    Article  CAS  PubMed  Google Scholar 

  13. Margulies, M. et al. Genome sequencing in microfabricated high-density picolitre reactors. Nature 437, 376–380 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Bentley, D. R. Whole-genome re-sequencing. Curr. Opin. Genet. Dev. 16, 545–552 (2006).

    Article  CAS  PubMed  Google Scholar 

  15. Marmur, J. & Doty, P. Thermal renaturation of deoxyribonucleic acids. J. Mol. Biol. 3, 585–594 (1961).

    Article  CAS  PubMed  Google Scholar 

  16. Davis, R. W. & Davidson, N. Electron-microscopic visualization of deletion mutations. Proc. Natl Acad. Sci. USA 60, 243–250 (1968). This paper is one of the first examples of whole-genome comparison using hybridization. The authors denatured bacteriophage DNA and visualized the renatured DNA using electron microscopy to identify genome deletions.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Southern, E. M. Detection of specific sequences among DNA fragments separated by gel electrophoresis. J. Mol. Biol. 98, 503–517 (1975). This reference is the original paper describing the Southern blot method of analysis.

    Article  CAS  PubMed  Google Scholar 

  18. Kafatos, F. C., Jones, C. W. & Efstratiadis, A. Determination of nucleic acid sequence homologies and relative concentrations by a dot hybridization procedure. Nucleic Acids Res. 7, 1541–1552 (1979).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Wallace, R. B. et al. Hybridization of synthetic oligodeoxyribonucleotides to φχ174 DNA: the effect of single base pair mismatch. Nucleic Acids Res. 6, 3543–3557 (1979).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Conner, B. J. et al. Detection of sickle cell β S-globin allele by hybridization with synthetic oligonucleotides. Proc. Natl Acad. Sci. USA 80, 278–282 (1983).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Maskos, U. & Southern, E. M. Oligonucleotide hybridizations on glass supports: a novel linker for oligonucleotide synthesis and hybridization properties of oligonucleotides synthesised in situ. Nucleic Acids Res. 20, 1679–1684 (1992).

    Article  CAS  PubMed  Google Scholar 

  22. Pease, A. C. et al. Light-generated oligonucleotide arrays for rapid DNA sequence analysis. Proc. Natl Acad. Sci. USA 91, 5022–5026 (1994).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Hughes, T. R. et al. Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer. Nature Biotechnol. 19, 342–347 (2001).

    Article  CAS  Google Scholar 

  24. Shalon, D., Smith, S. J. & Brown, P. O. A DNA microarray system for analyzing complex DNA samples using two-color fluorescent probe hybridization. Genome Res. 6, 639–645 (1996).

    Article  CAS  PubMed  Google Scholar 

  25. Wong, C. W. et al. Tracking the evolution of the SARS coronavirus using high-throughput, high-density resequencing arrays. Genome Res. 14, 398–405 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Chee, M. et al. Accessing genetic information with high-density DNA arrays. Science 274, 610–614 (1996). This paper describes a large advance in microarray manufacture and analysis: over 100,000 probes were synthesized on an array, which was used to probe sequence diversity in the human mitochondrial genome.

    Article  CAS  PubMed  Google Scholar 

  27. Maitra, A. et al. The human MitoChip: a high-throughput sequencing microarray for mitochondrial mutation detection. Genome Res. 14, 812–819 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Ishkanian, A. S. et al. A tiling resolution DNA microarray with complete coverage of the human genome. Nature Genet. 36, 299–303 (2004). This paper describes the first complete coverage of the human genome using a BAC microarray.

    Article  CAS  PubMed  Google Scholar 

  29. Fiegler, H. et al. Accurate and reliable high-throughput detection of copy number variation in the human genome. Genome Res. 16, 1566–1574 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. David, L. et al. A high-resolution map of transcription in the yeast genome. Proc. Natl Acad. Sci. USA 103, 5320–5325 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Gresham, D. et al. Genome-wide detection of polymorphisms at nucleotide resolution with a single DNA microarray. Science 311, 1932–1936 (2006).

    Article  CAS  PubMed  Google Scholar 

  32. Zhang, X. et al. Genome-wide high-resolution mapping and functional analysis of DNA methylation in Arabidopsis. Cell 126, 1189–1201 (2006).

    Article  CAS  PubMed  Google Scholar 

  33. Clark, R. M. et al. Common sequence polymorphisms shaping genetic diversity in Arabidopsis thaliana. Science 317, 338–342 (2007).

    Article  CAS  PubMed  Google Scholar 

  34. Hinds, D. A. et al. Whole-genome patterns of common DNA variation in three human populations. Science 307, 1072–1079 (2005). This paper presents the data from probing the entire human genome for sequence diversity using resequencing microarrays.

    Article  CAS  PubMed  Google Scholar 

  35. Feuk, L., Marshall, C. R., Wintle, R. F. & Scherer, S. W. Structural variants: changing the landscape of chromosomes and design of disease studies. Hum. Mol. Genet. 15, R57–R66 (2006).

    Article  CAS  PubMed  Google Scholar 

  36. Craven, S. H. & Neidle, E. L. Double trouble: medical implications of genetic duplication and amplification in bacteria. Future Microbiol. 2, 309–321 (2007).

    Article  CAS  PubMed  Google Scholar 

  37. Lupski, J. R. Genomic rearrangements and sporadic disease. Nature Genet. 39, S43–S47 (2007).

    Article  CAS  PubMed  Google Scholar 

  38. Bishop, J. M. The molecular genetics of cancer. Science 235, 305–311 (1987).

    Article  CAS  PubMed  Google Scholar 

  39. Pinkel, D. et al. High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nature Genet. 20, 207–211 (1998).

    Article  CAS  PubMed  Google Scholar 

  40. Pollack, J. R. et al. Genome-wide analysis of DNA copy-number changes using cDNA microarrays. Nature Genet. 23, 41–46 (1999). References 39 and 40 demonstrate the application of comparative genomic hybridization of human DNA using microarrays to identify amplified genes.

    Article  CAS  PubMed  Google Scholar 

  41. Dunham, M. J. et al. Characteristic genome rearrangements in experimental evolution of Saccharomyces cerevisiae. Proc. Natl Acad. Sci. USA 99, 16144–16149 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Lucito, R. et al. Genetic analysis using genomic representations. Proc. Natl Acad. Sci. USA 95, 4487–4492 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Iafrate, A. J. et al. Detection of large-scale variation in the human genome. Nature Genet. 36, 949–951 (2004).

    Article  CAS  PubMed  Google Scholar 

  44. Sebat, J. et al. Large-scale copy number polymorphism in the human genome. Science 305, 525–528 (2004). References 43 and 44 report the surprisingly large extent of copy number variation in the human genome.

    Article  CAS  PubMed  Google Scholar 

  45. Stankiewicz, P. & Beaudet, A. L. Use of array CGH in the evaluation of dysmorphology, malformations, developmental delay, and idiopathic mental retardation. Curr. Opin. Genet. Dev. 17, 182–192 (2007).

    Article  CAS  PubMed  Google Scholar 

  46. Sebat, J. et al. Strong association of de novo copy number mutations with autism. Science 316, 445–449 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Weiss, L. A. et al. Association between microdeletion and microduplication at 16p11.2 and autism. N. Engl. J. Med. 358, 667–675 (2008).

    Article  CAS  PubMed  Google Scholar 

  48. Brown, C. J., Todd, K. M. & Rosenzweig, R. F. Multiple duplications of yeast hexose transport genes in response to selection in a glucose-limited environment. Mol. Biol. Evol. 15, 931–942 (1998).

    Article  CAS  PubMed  Google Scholar 

  49. Hughes, T. R. et al. Widespread aneuploidy revealed by DNA microarray expression profiling. Nature Genet. 25, 333–337 (2000).

    Article  CAS  PubMed  Google Scholar 

  50. Maydan, J. S. et al. Efficient high-resolution deletion discovery in Caenorhabditis elegans by array comparative genomic hybridization. Genome Res. 17, 337–347 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Graubert, T. A. et al. A high-resolution map of segmental DNA copy number variation in the mouse genome. PLoS Genet. 3, e3 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Olshen, A. B., Venkatraman, E. S., Lucito, R. & Wigler, M. Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics 5, 557–572 (2004).

    Article  PubMed  Google Scholar 

  53. Marioni, J. C., Thorne, N. P. & Tavare, S. BioHMM: a heterogeneous hidden Markov model for segmenting array CGH data. Bioinformatics 22, 1144–1146 (2006).

    Article  CAS  PubMed  Google Scholar 

  54. Barrett, M. T. et al. Comparative genomic hybridization using oligonucleotide microarrays and total genomic DNA. Proc. Natl Acad. Sci. USA 101, 17765–17770 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Selzer, R. R. et al. Analysis of chromosome breakpoints in neuroblastoma at sub-kilobase resolution using fine-tiling oligonucleotide array CGH. Genes Chromosomes Cancer 44, 305–319 (2005).

    Article  CAS  PubMed  Google Scholar 

  56. Urban, A. E. et al. High-resolution mapping of DNA copy alterations in human chromosome 22 using high-density tiling oligonucleotide arrays. Proc. Natl Acad. Sci. USA 103, 4534–4539 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Redon, R. et al. Global variation in copy number in the human genome. Nature 444, 444–454 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Weir, B. A. et al. Characterizing the cancer genome in lung adenocarcinoma. Nature 450, 893–898 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Korbel, J. O. et al. Paired-end mapping reveals extensive structural variation in the human genome. Science 318, 420–426 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Fan, J. B., Chee, M. S. & Gunderson, K. L. Highly parallel genomic assays. Nature Rev. Genet. 7, 632–644 (2006).

    Article  CAS  PubMed  Google Scholar 

  61. Kallioniemi, O. P. Biochip technologies in cancer research. Ann. Med. 33, 142–147 (2001).

    Article  CAS  PubMed  Google Scholar 

  62. Maskos, U. & Southern, E. M. Parallel analysis of oligodeoxyribonucleotide (oligonucleotide) interactions. I. Analysis of factors influencing oligonucleotide duplex formation. Nucleic Acids Res. 20, 1675–1678 (1992).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Hacia, J. G., Brody, L. C., Chee, M. S., Fodor, S. P. & Collins, F. S. Detection of heterozygous mutations in BRCA1 using high density oligonucleotide arrays and two-colour fluorescence analysis. Nature Genet. 14, 441–447 (1996).

    Article  CAS  PubMed  Google Scholar 

  64. Winzeler, E. A. et al. Direct allelic variation scanning of the yeast genome. Science 281, 1194–1197 (1998). In this paper, the authors discover sequence variation across the yeast genome using an Affymetrix microarray that was designed to assess gene expression.

    Article  CAS  PubMed  Google Scholar 

  65. Borevitz, J. O. et al. Large-scale identification of single-feature polymorphisms in complex genomes. Genome Res. 13, 513–523 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Turner, T. L., Hahn, M. W. & Nuzhdin, S. V. Genomic islands of speciation in Anopheles gambiae. PLoS Biol. 3, e285 (2005).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  67. Albert, T. J. et al. Mutation discovery in bacterial genomes: metronidazole resistance in Helicobacter pylori. Nature Methods 2, 951–953 (2005).

    Article  CAS  PubMed  Google Scholar 

  68. Herring, C. D. et al. Comparative genome sequencing of Escherichia coli allows observation of bacterial evolution on a laboratory timescale. Nature Genet. 38, 1406–1412 (2006).

    Article  CAS  PubMed  Google Scholar 

  69. Schacherer, J. et al. Genome-wide analysis of nucleotide-level variation in commonly used Saccharomyces cerevisiae strains. PLoS ONE 2, e322 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  70. Cutler, D. J. et al. High-throughput variation detection and genotyping using microarrays. Genome Res. 11, 1913–1925 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Kleckner, N. Transposable elements in prokaryotes. Annu. Rev. Genet. 15, 341–404 (1981).

    Article  CAS  PubMed  Google Scholar 

  72. Muotri, A. R. et al. Somatic mosaicism in neuronal precursor cells mediated by L1 retrotransposition. Nature 435, 903–910 (2005).

    Article  CAS  PubMed  Google Scholar 

  73. Babushok, D. V. & Kazazian, H. H. Jr. Progress in understanding the biology of the human mutagen LINE-1. Hum. Mutat. 28, 527–539 (2007).

    Article  CAS  PubMed  Google Scholar 

  74. Liti, G., Peruffo, A., James, S. A., Roberts, I. N. & Louis, E. J. Inferences of evolutionary relationships from a population survey of LTR-retrotransposons and telomeric-associated sequences in the Saccharomyces sensu stricto complex. Yeast 22, 177–192 (2005).

    Article  CAS  PubMed  Google Scholar 

  75. Gabriel, A. et al. Global mapping of transposon location. PLoS Genet. 2, e212 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  76. Blanc, V. M. & Adams, J. Evolution in Saccharomyces cerevisiae: identification of mutations increasing fitness in laboratory populations. Genetics 165, 975–983 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  77. Aminetzach, Y. T., Macpherson, J. M. & Petrov, D. A. Pesticide resistance via transposition-mediated adaptive gene truncation in Drosophila. Science 309, 764–767 (2005).

    Article  CAS  PubMed  Google Scholar 

  78. Wilke, C. M. & Adams, J. Fitness effects of Ty transposition in Saccharomyces cerevisiae. Genetics 131, 31–42 (1992).

    CAS  PubMed  PubMed Central  Google Scholar 

  79. Chisholm, G. E. & Cooper, T. G. Ty insertions upstream and downstream of native DUR1,2 promoter elements generate different patterns of DUR1,2 expression in Saccharomyces cerevisiae. J. Bacteriol. 174, 2548–2559 (1992).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Kellis, M., Birren, B. W. & Lander, E. S. Proof and evolutionary analysis of ancient genome duplication in the yeast Saccharomyces cerevisiae. Nature 428, 617–624 (2004).

    Article  CAS  PubMed  Google Scholar 

  81. Wheelan, S. J., Scheifele, L. Z., Martinez-Murillo, F., Irizarry, R. A. & Boeke, J. D. Transposon insertion site profiling chip (TIP-chip). Proc. Natl Acad. Sci. USA 103, 17632–17637 (2006). Together with reference 75 this paper demonstrates the use of selective extraction of endogenous insertion sequences and their physical mapping using microarrays.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Riley, J. et al. A novel, rapid method for the isolation of terminal sequences from yeast artificial chromosome (YAC) clones. Nucleic Acids Res. 18, 2887–2890 (1990).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Badarinarayana, V. et al. Selection analyses of insertional mutants using subgenic-resolution arrays. Nature Biotechnol. 19, 1060–1065 (2001).

    Article  CAS  Google Scholar 

  84. Kumar, A. et al. Large-scale mutagenesis of the yeast genome using a Tn7-derived multipurpose transposon. Genome Res. 14, 1975–1986 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Smith, V., Chou, K. N., Lashkari, D., Botstein, D. & Brown, P. O. Functional analysis of the genes of yeast chromosome V by genetic footprinting. Science 274, 2069–2074 (1996).

    Article  CAS  PubMed  Google Scholar 

  86. Amsterdam, A. & Hopkins, N. Retroviral-mediated insertional mutagenesis in zebrafish. Methods Cell Biol. 77, 3–20 (2004).

    Article  CAS  PubMed  Google Scholar 

  87. Dupuy, A. J., Akagi, K., Largaespada, D. A., Copeland, N. G. & Jenkins, N. A. Mammalian mutagenesis using a highly mobile somatic Sleeping Beauty transposon system. Nature 436, 221–226 (2005).

    Article  CAS  PubMed  Google Scholar 

  88. Girgis, H. S., Liu, Y., Ryu, W. S. & Tavazoie, S. A comprehensive genetic characterization of bacterial motility. PLoS Genet. 3, 1644–1660 (2007).

    Article  CAS  PubMed  Google Scholar 

  89. Salama, N. R., Shepherd, B. & Falkow, S. Global transposon mutagenesis and essential gene analysis of Helicobacter pylori. J. Bacteriol. 186, 7926–7935 (2004). Together with references 83 and 88, this paper illustrates the use of microarrays to characterize pools of mutants that were generated using artificial transposons.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Johnson, D. S., Mortazavi, A., Myers, R. M. & Wold, B. Genome-wide mapping of in vivo protein–DNA interactions. Science 316, 1497–1502 (2007).

    Article  CAS  PubMed  Google Scholar 

  91. Robertson, G. et al. Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing. Nature Methods 4, 651–657 (2007).

    Article  CAS  PubMed  Google Scholar 

  92. Patterson, T. A. et al. Performance comparison of one-color and two-color platforms within the MicroArray Quality Control (MAQC) project. Nature Biotechnol. 24, 1140–1150 (2006).

    Article  CAS  Google Scholar 

  93. Song, J. S. et al. Microarray blob-defect removal improves array analysis. Bioinformatics 23, 966–971 (2007).

    Article  CAS  PubMed  Google Scholar 

  94. Bolstad, B. M., Irizarry, R. A., Astrand, M. & Speed, T. P. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19, 185–193 (2003).

    Article  CAS  PubMed  Google Scholar 

  95. Rosenzweig, B. A. et al. Dye bias correction in dual-labeled cDNA microarray gene expression measurements. Environ. Health Perspect. 112, 480–487 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Kelley, R., Feizi, H. & Ideker, T. Correcting for gene-specific dye bias in DNA microarrays using the method of maximum likelihood. Bioinformatics 24, 71–77 (2008).

    Article  CAS  PubMed  Google Scholar 

  97. Torres, E. M. et al. Effects of aneuploidy on cellular physiology and cell division in haploid yeast. Science 317, 916–924 (2007).

    Article  CAS  PubMed  Google Scholar 

  98. Omura, F., Hatanaka, H. & Nakao, Y. Characterization of a novel tyrosine permease of lager brewing yeast shared by Saccharomyces cerevisiae strain RM11–11a. FEMS Yeast Res. 7, 1350–1361 (2007).

    Article  CAS  PubMed  Google Scholar 

  99. Wang, D. et al. Viral discovery and sequence recovery using DNA microarrays. PLoS Biol. 1, e2 (2003). This paper is the first to use microarrays to identify and enrich for specific sequences that are subsequently analyzed using direct sequencing.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  100. Hodges, E. et al. Genome-wide in situ exon capture for selective resequencing. Nature Genet. 39, 1522–1527 (2007).

    Article  CAS  PubMed  Google Scholar 

  101. Okou, D. T. et al. Microarray-based genomic selection for high-throughput resequencing. Nature Methods 4, 907–909 (2007).

    Article  CAS  PubMed  Google Scholar 

  102. Albert, T. J. et al. Direct selection of human genomic loci by microarray hybridization. Nature Methods 4, 903–905 (2007). References 100–102 use whole-genome microarrays to selectively enrich the coding fraction of the human genome for subsequent analysis using high-throughput sequencing methods.

    Article  CAS  PubMed  Google Scholar 

  103. Palmer, C., Bik, E. M., Digiulio, D. B., Relman, D. A. & Brown, P. O. Development of the human infant intestinal microbiota. PLoS Biol. 5, e177 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  104. Gill, S. R. et al. Metagenomic analysis of the human distal gut microbiome. Science 312, 1355–1359 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Sjoblom, T. et al. The consensus coding sequences of human breast and colorectal cancers. Science 314, 268–274 (2006).

    Article  PubMed  CAS  Google Scholar 

  106. Wood, L. D. et al. The genomic landscapes of human breast and colorectal cancers. Science (2007).

  107. Schroder, A. R. et al. HIV-1 integration in the human genome favors active genes and local hotspots. Cell 110, 521–529 (2002).

    Article  CAS  PubMed  Google Scholar 

  108. Hoheisel, J. D. Microarray technology: beyond transcript profiling and genotype analysis. Nature Rev. Genet. 7, 200–210 (2006).

    Article  CAS  PubMed  Google Scholar 

  109. Perry, G. H. et al. Diet and the evolution of human amylase gene copy number variation. Nature Genet. 39, 1256–1260 (2007).

    Article  CAS  PubMed  Google Scholar 

  110. Saldanha, A. J. Java Treeview — extensible visualization of microarray data. Bioinformatics 20, 3246–3248 (2004).

    Article  CAS  PubMed  Google Scholar 

  111. Saeed, A. I. et al. TM4 microarray software suite. Methods Enzymol. 411, 134–193 (2006).

    Article  CAS  PubMed  Google Scholar 

  112. Gentleman, R. C. et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 5, R80 (2004).

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank members of the Botstein and Dunham laboratories. Research is supported by the National Institute of General Medical Sciences Center for Quantitative Biology (GM-071508) grant.

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Glossary

Experimental evolution

The long-term selection of microorganisms or populations under laboratory conditions to model simple evolutionary scenarios.

Detect

The identification of a genomic variant, the actual state of which is not known until further analysis.

DNA probe

In the context of microarrays, DNA probe refers to the DNA oligonucleotide, PCR product or genomic clone that is attached to a microarray in order to probe a labelled genomic DNA sample that is added in solution. In the context of Southern blotting, DNA probe refers to the labelled DNA oligonucleotide that is added in solution to probe the genomic DNA sample that is immobilized on a membrane.

Photolithography

The use of masks to selectively deprotect nascent oligonucleotides using light, allowing the parallel synthesis of millions of probes.

Ink-jet deposition

The use of print cartridge heads to deposit one of the four DNA bases at a probe site on the microarray.

Fluorescent in situ hybridization

(FISH). A technique in which a fluorescently labelled DNA probe is used to detect a particular chromosome or gene using fluorescence microscopy.

Quantitative PCR

A procedure in which the products of a PCR reaction are measured by monitoring the signal that is produced by a fluorescent dye, which accumulates during each PCR cycle.

Tm

The Tm (melting temperature) of an oligonucleotide is the temperature at which 50% of the duplex strands are separated.

Suppressor mutations

Mutations that suppress, or alleviate, the phenotypic effect of another mutation.

Genome complexity

The number of different DNA sequences in a genome, originally measured by the rate of re-association of heat-denatured DNA.

Paired-end sequencing

Determination of the sequence at both ends of a fragment of DNA of known size.

Resequencing

The determination of the exact DNA sequence by comparison with a known reference.

Parametric tests

Statistical tests that assume an underlying distribution, which is usually Gaussian. The term Gaussian describes a continuous probability distribution that is symmetrical around a defined mean value, the shape of which is determined by the variance.

Chromatin immunoprecipitation

(ChIP). Fractionation of DNA that is bound to a protein of interest by means of an antibody.

Ratiometric approach

The use of methods that include an internal reference so that the ratio between sample and control is the metric of interest.

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Gresham, D., Dunham, M. & Botstein, D. Comparing whole genomes using DNA microarrays. Nat Rev Genet 9, 291–302 (2008). https://doi.org/10.1038/nrg2335

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