“With next-generation sequencing, repetitive regions can now be surveyed to a large extent,” explains Peter J. Park, Ph.D., assistant professor at Harvard Medical School. Dr. Park and collaborators are using next-generation sequencing to compare the genome from diseased individuals with the genome from healthy individuals, and this approach promises to identify repetitive region changes that are associated with malignancy.
This endeavor is catalyzed by the fact that whole-genome sequencing has become much more affordable in recent years. “Sequencing a genome used to cost millions of dollars three to four years ago, and it can be done for $10,000 right now,” remarks Dr. Park. “There will be a lot of interest in this field in the next few years, because we know very little about these repetitive sequences, but there are diseases where changes in these regions cause undesirable phenotypes,” he explains.
“The most important question is what you are looking for,” explains Francis Galibert, Ph.D., emeritus professor at the University of Rennes and senior scientist at the Centre National de la Recherche Scientifique. Dr. Galibert and collaborators are using both microarrays and deep sequencing, and noticed that sequencing might be better to survey genes that are poorly expressed, particularly when gene-expression changes between two distinct biological conditions that are examined are small.
“But for this to happen you need very, very deep RNA sequencing, so that the genes you are interested in are counted enough times. And this is better achieved if you performed 3´ Tag sequencing instead of RNA full-length sequencing,” explains Dr. Galibert. One of the projects in the Galibert lab examines RNA expression changes in the rat olfactory bulb and olfactory epithelia over time, and also responses to specific environmental exposures.
In rats exposed to different odorants, the investigators noticed that specific odorants modify the number of transcripts corresponding to the receptor to which they bind. “But the changes are very subtle and quite difficult to detect, and one needs a large number of experiments that have to be repeated a few times. And for this particular application, I thought that sequencing might be more accurate,” explains Dr. Galibert.
“Next-generation sequencing has several advantages if properly implemented and, among other things, it is more accurate and more comprehensive than oligonucleotide hybridization-based sequencing,” says Heidi L. Rehm, Ph.D., assistant professor of pathology at Harvard Medical School and chief laboratory director at the Laboratory for Molecular Medicine at Partners Healthcare Center for Personalized Genetic Medicine.
Approximately three years ago, the Laboratory for Molecular Medicine launched one of the first hybridization-based sequencing services intended for clinical use. One of the shortcomings of hybridization approaches is their difficulty to detect insertions and deletions, and their inability to visualize copy-number variations.
Next-generation sequencing can reveal these types of changes, and Dr. Rehm and collaborators are currently developing next-generation sequencing-based applications for use in the clinical lab—but these, too, are anticipated to bring their own set of specific challenges.
“There are so many ways to conduct next-generation sequencing, in terms of protocols, instruments, libraries, barcodes, and all the different capture methods, and these all represent essential aspects in terms of what to get out of the test,” explains Dr. Rehm. “It is a very complex system to develop, and it requires a huge amount of hardware for data storage and bioinformatics support,” she adds.
“We use microarrays for detecting microorganisms, and also for measuring their metabolic activities,” explains Michael Wagner, Ph.D., head of the department of microbial ecology at the University of Vienna, Austria. Dr. Wagner and colleagues are using microarrays to examine ribosomal RNA genes and simultaneously detect multiple microorganisms from complex clinical or environmental samples. This approach has important implications for diagnostics and environmental monitoring.
“This kind of application can also be done by next-generation sequencing, which is less targeted and much more expensive, but microarrays are faster and cheaper when the goal is to detect previously recognized microorganisms. It all depends on the type of questions that one wants to address,” emphasizes Dr. Wagner.
In addition to detecting microorganisms, this approach also opens the possibility to obtain information about the in situ metabolic activity of the microorganisms that are being surveyed.
The tool, which is called isotope array and was developed by Dr. Wagner and colleagues several years ago, involves adding an isotope-labeled substrate to the sample, and examining the isotope incorporation into the ribosomal RNA by active microorganisms. Microarray analysis can subsequently be informative not only with respect to the identity of the microorganisms that are present, but also about their metabolic activity. This approach is even more valuable, considering that most microorganisms cannot be cultured in the lab.
“If the goal is to conduct highly parallel functional studies, and learn not only which microorganisms are there but also what they are doing, then microarrays cannot be replaced. Both microarray platforms and sequencing methodologies have their specific niches, where they complement each other,” emphasizes Dr. Wagner.
Microarrays and sequencing have emerged as powerful tools that are revolutionizing the life sciences and continue to promise new perspectives in research and medicine. Each presents certain advantages and opens a number of challenges. It is the need to implement these tools in a manner that is most effective, most informative, and carefully tailored to the scientific question and the biological system that is being surveyed that emerges as the most memorable take-home lesson.