Human chromosomes are intricate and dynamic structures. Along the length of a chromosome’s DNA are regions encoding proteins, sequences regulating gene expression, pieces of viral DNA that infected our ancient ancestors, segments with epigenetic changes that can functionally hide that DNA, and more that isn’t yet understood. Chromosomes must be able to unwind to a mass of DNA thread spread out in an operationally purposeful way, and then coil back into a tightly wound packet. With all this complexity, there is an army of proteins moving all around inside the nuclear matrix defending, repairing and rebuilding our DNA against constant damage. Nevertheless, the breaks and inadvertent modifications that inevitably happen to our DNA do lead to sometimes large alterations to the structure of our chromosomes. This structural variation can have wide-ranging implications for disease, phenotype and for long-term evolutionary changes in our species, making detection critical.

Firstly, it is useful to define structural variants (SV). SV’s can be divided into two overlapping categories. The first includes SV’s which change how many copies of a DNA segment there are in the genome. These are copy number variants (CNV). The DNA segment in question can range in size from a single base – single nucleotide variations (SNV) – to a large portion of a chromosome, encompassing many millions of bases. Changes in the number of whole homologs for a given chromosome, known as aneuploidy, represent a numerical change rather than a structural one. The other broad category of SV’s includes those which change the location of the affected region. Two good examples of this are inversions and balanced translocations. A DNA segment reverses its orientation with respect to the rest of the chromosome in an inversion, and an affected segment relocates to another chromosome in a translocation. The overlap mentioned between the two categories of SV’s is showcased in the case of translocations, as they can be balanced or unbalanced. Balanced translocations relocate DNA without causing any gain or loss of DNA, whereas unbalanced translocations do change the copy number of part of the affected region. Many other types of SV’s exist, such as insertions, deletions, duplications, tandem repeats, and more.

As mentioned, SV’s can impact health, phenotype and even the evolution of the species. Methods to accurately quantify and qualify the changes then have high value, but not all can be measured as easily. Single base pair changes can be measured using sequencing tools, but those tools sequence fragments, meaning that detecting larger structural changes can be more challenging because it involves aligning numerous short sequence fragments. Aligning hundreds of millions of fragment reads can make it harder to detect specific rearrangements due to their unique characteristics. Microarray is one platform which can cost-effectively detect CNV’s, but it is unable to reliably spot balanced translocations, in which segments of different chromosomes swap places without an overall change in genetic material. Next-generation sequencing (NGS), struggles to resolve complex repeat regions, as the short sequence reads may not be sufficient to span these regions effectively. Moreover, technologies like optical mapping and nanopore sequencing, while promising for certain SVs, may face challenges in accurately detecting the full spectrum of structural rearrangements. Directional Genomic Hybridization (dGH™), though unable to detect SNV’s, can detect rearrangements a few kilobases in size, including inversions.

These complexities highlight the importance of integrating multiple technologies and analytical approaches to comprehensively assay structural variants in the genome. Each method comes with its own strengths and limitations. Sequencing offers insight into single base pair changes, but detecting complex structural rearrangements presents its own set of obstacles. The unique data needs of a given research endeavor must be the basis from which to select one or more platforms with which to achieve the desired scientific goals.