Technological advances in genetic analysis methods have greatly expanded cytogenetic analysis options in recent years, pushing the boundaries of what is practical and possible in clinical research settings. These advances have made numerous kinds of genetic abnormalities increasingly simple to recognize.
With this proliferation of methods comes a new challenge for researchers: selecting the most optimal method for their research laboratory. Choosing between the many options currently available is no small task. This rundown provides the basics of the most common options.
Comparison of genetic analysis methods
Current methods of chromosomal analysis fall into two broad categories: chromosomal microarrays and next-generation sequencing.
Chromosomal microarrays
Chromosomal microarray analysis (CMA) is widely used to study specific chromosomal aberrations. This genetic analysis method typically consists of a solid matrix carrying a defined set of nucleic acid fragments that serve as probes for their DNA complements. DNA from a sample, typically labeled with fluorescent tags, is allowed to hybridize, or not, with the probes and the excess is washed away.
The fluorescence that persists after this wash shows which probe sequences on the microarray are present in the sample and in what relative quantities. CMA is especially well-suited to detecting copy-number variations (CNVs), which are variations in the number of copies of a genomic region of interest, but can also detect single-nucleotide variations (SNVs), which are single-base-pair differences.
User-friendly and flexible analysis software interpreting and reporting the results of CMA are standardized and readily available. Combined with the relative versatility and ease of use of CMA in general and the versatile analysis software available for this technique, CMA is a powerful genetic analysis tool.
The most advanced arrays are hybrid-SNP arrays which combine the best features of aCGH and SNP arrays. These are high-resolution and high-density with up to seven million polymorphic (SNP) and non-polymorphic (copy number) probes. These higher-density arrays give greater confidence to accurately identify copy-neutral aberrations compared to non-hybrid arrays. This makes these arrays especially well-suited to genomic abnormalities that often elude other sorts of arrays, including mosaicism, triploidy, and consanguinity.
Next-generation sequencing
When further insight is needed, next-generation sequencing (NGS) can be paired with CMA or used separately. Regardless of the specifics, next-generation sequencing works in broadly the same way.
First, a genome is fragmented into a library of pieces and amplified.
Then, those pieces are sequenced and digitally reassembled using software. Sequencing with fragments rather than the whole, intact genome enables the wet-lab portion of a sequencing event to be done massively in parallel, making NGS much faster than some methods. By comparing the results of NGS to a reference genome, aberrations of interest can be flagged en masse, be they deletions, insertions, duplications, or something else.
The digital tools available for use with NGS continue to improve, making this technique more and more useful for more and more complex genomic situations. NGS can be done at the level of the entire genome, but it can also be performed specifically on the collected body of exons, the exome, for exome sequencing. Exome sequencing is much faster and less expensive than whole-genome sequencing but might miss aberrations associated with non-coding DNA, which is the majority of all DNA. NGS is typically the province of bioinformaticians and not something a laboratory can pick up without dedicated expertise.
Recommendations for choosing a genetic analysis method
Professional societies keep their own counsel regarding genomic analysis methods. Most societies including American College of Genetics (ACMG) and American College of Obstetricians and Gynecologists (ACOG) recommend CMA to study genetic disorders or reveal that a situation is complex enough to warrant NGS.
Which genetic analysis technology is the optimal choice for a given research laboratory depends on numerous factors, including but not limited to:
- Data quality, which is affected by the kinds of aberrations one is interested in exploring and, from there, which analytical methods best illuminate those specific differences.
- Resources, which include ability to store the large amount of data some methods generate, space for laboratory instruments, funds for procuring instruments and reagents, and ability to hire and retain bioinformatics expertise.
- Time, in particular the desired turnaround time for results. Some methods are faster than others and some samples prioritize speed more than others, such as prenatal genetic prenatal genetic research.
- Cost, which is affected by throughput for all methods. NGS is more expensive than chromosomal microarrays in general and can only approach the cost per sample of microarrays with very high throughput.
- Technical considerations, in particular whether a research laboratory has the expertise to sort through potentially superfluous findings in a high-data method to find variations of interest.
Combining analysis methods for comprehensive genomic research
Often, the best course of action is to use relatively inexpensive analysis methods as an initial effort and add other analysis tools as needed to clarify or augments the results thereof. In this way, the most expensive, time-consuming, and difficult-to-process methods are reserved for situations that justify their outlay. Combining analysis methods from the start, such as using well-chosen CMA alongside whole-genome sequencing, can also yield a large amount of data quickly and help research difficult cases faster than doing analyses in sequence, but requires a research laboratory with substantial resources.
Conclusion
CMA and NGS are both powerful genomic analysis methods with a variety of sub-methods. Studying chromosomal aberrations can work with any of these methods, but each one is best suited to specific situations. Chromosomal microarrays are an established, robust, low-resource technique that is also more limited than NGS and choosing a specific kind of microarray can be tricky when they all work differently. Conversely, NGS is a powerful method that is expensive and time-consuming to implement and generates an enormous amount of potentially superfluous data to sort through, requiring expertise to use well. Many use cases benefit from combining methods. The decision of which method or methods to use depends on the particulars of a given research laboratory’s use case and can only ever be an individual choice. There is no one-size-fits-all method, but between them all, most can be accommodated.
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