Single gene-focused research can sometimes be like the Indian story of the blind men and the elephant. The blind men, having never seen an elephant before, decide to touch one and feel it for themselves, to determine its shape. However, since they all grab different parts of the elephant, each can only describe what they feel, and none of them has the full picture of how exactly an elephant looks.
Genes, such as microRNAs, tend to operate in organized complex networks, and the ability to study them in their native states has been quite technically challenging. Current combinatorial techniques for interactive network studies are limited in resolution and complexity, and they can only perform up to pairwise interaction analysis. These techniques also require substantial time investment in analysis and experimental design.
To overcome these limitations, Alan Wong and colleagues in Timothy Lu’s lab at MIT designed and developed a scalable technique to create barcoded libraries of high-order combinations of genetic elements that can be quantified with high-throughput sequencing. Their approach comprehensively characterizes high-order genetic interactions in a high-throughput fashion via an iterative cloning system. It all begins with an insert library of barcoded DNA elements.
Next, an enzymatic digestion of the pooled insert libraries, including destination vectors, followed by a one-pot ligation step, generates the combinatorial genetic library. This combination library and its insert pool “can be combined to generate higher-order combinations with concatenated barcodes that are unique for each combination, thus enabling tracking using high-throughput sequencing”.
The technology, codenamed CombiGEM (combinatorial genetics en masse), was employed to create:
- 1,521 two-wise high-resolution libraries and 51,770 three-wise barcoded combinations of 39 human microRNA (miRNA) precursors.
- Additionally, the researchers identified microRNA combinations that synergistically sensitize drug-resistant cancer cells to chemotherapy or inhibit cancer cell proliferation, thus providing insights into complex miRNA networks.
The researchers hope that their technology will help reveal complex interactions between multiple genetic components, possibly leading to better diagnosis, treatment, bioengineering, and all-around understanding.
Explore how to make your own combinatorial genetic library using CombiGEM at Nature Biotechnology August, 2015