Jeffrey Perkel has been a scientific writer and editor since 2000. He holds a PhD in Cell and Molecular Biology from the University of Pennsylvania, and did postdoctoral work at the University of Pennsylvania and at Harvard Medical School.
The human genome is often referred to as a “blueprint.” And it is, in a sense. The genome contains all the information required to build and run a cell, tissue, or organism. But whereas blueprints are invariant, the genome is anything but.
As they grow and divide, as they differentiate and form gametes, cells’ genetic material acquires changes. Sometimes those are single-base changes; and sometimes those changes occur on a larger-scale, anything from short insertions and deletions of a handful of bases (“indels”) to large structural alterations such as inversions, deletions, insertions, and translocations. These architectural polymorphisms play an outsized role in human genetic variation from stem cells to cancer—a field of research broadly termed “cytogenetics” —and there exists a broad set of tools to study them at size scales from the single nucleotide to the chromosomal level.
Giemsa/Chromosome painting
For the coarsest resolution view of the genome, researchers use classical microscopy techniques, like karyotyping and FISH. Giemsa staining of compacted metaphase chromosomes induces characteristic black-and-white banding patterns that are visible under a light microscope—an analysis called karyotyping. Skilled researchers using such a technique can detect large-scale alterations in an individual’s karyotype, on the order of megabases or more—changes such as variation in chromosome number (aneuploidy), chromosomal fusions, large-scale insertions and deletions, and translocations.
Fluorescence in-situ hybridization (FISH) applies molecular specificity to cytogenetic analysis. With FISH, researchers use fluorescently labeled nucleic acid probes to determine (under a microscope) on which chromosome one or a few specific gene sequences are located, and if they have been moved, amplified, or deleted. Chromosome “painting” is a form of FISH in which chromosome-specific fluorescent probes are used to light-up specific chromosomes, or regions of chromosomes.
Painting reagents are available in a variety of configurations. For instance, Applied Spectral Imaging’s SKY Painting Probes can label every human, mouse, or rat chromosome a unique color simultaneously, whereas its single whole chromosome painting probes target specific chromosomes individually. Cambio’s Star*FISH probes are available in whole-chromosome, centromere-specific, and telomere-specific versions for both single and pan-chromosomal studies.
SNP/CNV microarrays
For higher-resolution work, researchers can use DNA microarrays to produce a so-called “virtual karyotype.” Such microarrays contain probes tiled across all or a fraction of the genome, and by comparing the hybridization intensity at each probe, cytogeneticists can determine whether specific regions are under- or over-represented—that is, deleted or amplified. (This type of analysis is called array-comparative genomic hybridization, aCGH.)
Virtual karyotyping is both technically simpler than traditional karyotyping, and higher resolution. Theoretically, a copy-number alteration impacting just a single probe on the array can be detected by this analysis (meaning the resolution would equal the array’s tiling density), but in practice, researchers generally set a threshold at alterations affecting several adjacent probes at once.
Virtual karyotyping microarrays may contain probes for detecting single-nucleotide polymorphisms (SNPs), copy-number variants (CNVs), or both, and how the assay works will vary based on its design. For instance, Affymetrix arrays have separate probes for each potential SNP variant, whereas Illumina BeadChips use a primer-extension assay to identify SNPs by color.
Affymetrix’s CytoScan® HD Array includes, according to company literature, 2.67 million CNV probes, 750,000 SNP probes, and 1.9 million “non-polymorphic probes for comprehensive whole-genome coverage.” Agilent Technologies and Oxford Gene Technology (OGT) also offer arrays covering both CNVs and SNPs, whereas Illumina focuses on SNP detection with its portfolio, including the HumanOmni5-Quad BeadChip microarray, which contains 4.3 million “fixed” markers and up to 500,000 custom probes.
Sequencing
In today’s genomics-centric world, there is of course another option for molecular cytogenetics: Next-generation DNA sequencing. Analysis of the density, position, or spacing of reads across a genome, assuming the sequencing is deep enough, can in theory pinpoint structural and copy-number variants, and do so at near-nucleotide resolution. (By comparison, array resolution is governed by tiling density, which can be on the order of kilobases.)
But that’s in theory. The variability inherent in next gen sequencing experiments makes converting reads into structural data a non-trivial exercise. Still, several strategies have been reported in the literature including CNV-seq, ABCD-DNA, CNVnvator, and cnvHiTSeq. [1-4] In December, Harvard researcher X. Sunney Xie even demonstrated that CNV analysis is possible at the single-cell level. [5]
Of course, when considering cytogenetics, remember that acquiring the technology costs money, and developing expertise takes time. For some labs, that initial expense makes sense. Others, though, can outsource the work to a university core facility or external service provider such as OGT, Signature Genomics, or Quest Diagnostics.
Bottom line: If you have the need to tackle cytogenetics, the tools exist to suit your needs, whether in-house or externally.
References
[1] Xie, C and Tammi, MT, “CNV-seq, a new method to detect copy number variation using high-throughput sequencing,” BMC Bioinformatics 10:80, 2009; doi:10.1186/1471-2105-10-80.
[2] Robinson, MD, et al., “Copy-number-aware differential analysis of quantitative DNA sequencing data,” Genome Research 22(12): 2489–2496, 2012; doi: 10.1101/gr.139055.112.
[3] Abyzov, A, et al., “CNVnator: An approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing,” Genome Research 21: 974-984, 2011; doi:10.1101/gr.114876.110.
[4] Bellos, E, et al., “cnvHiTSeq: integrative models for high-resolution copy number variation detection and genotyping using population sequencing data,” Genome Biology 13:R120, 2012; doi:10.1186/gb-2012-13-12-r120.
[5] Zong, C. et al., “Genome-Wide Detection of Single-Nucleotide and Copy-Number Variations of a Single Human Cell,” Science 21, Vol. 338 no. 6114 pp. 1622-1626, 2012; DOI: 10.1126/science.1229164.