Author interview: Sudarshan Pinglay leads a research lab at the University of Washington, Department of Genome Sciences and the Brotman Baty Institute for Precision Medicine. He received his PhD for research conducted in the labs of Jef Boeke and Liam Holt at NYU. Sudarshan developed tools for the “re-writing” of mammalian genomes through the synthesis of large DNA constructs and their targeted integration into cells. These tools are being applied to: 1) understand how genes are turned on and off; and 2) endow cells with sophisticated behaviors not found in nature. He is from Bangalore, India and completed undergraduate degrees in molecular biology and philosophy at Johns Hopkins University. Sudarshan is passionate about soccer, heavy metal guitar, food and sharing the joys of a scientific worldview.
We developed Genome-Shuffle-seq, a method to induce and analyze structural variants in mammalian genomes at single-cell resolution, enabling insights into the impact of genome rearrangements in development and disease contexts.
Interview
What was the core problem you aimed to solve with this research?
Structural variants (SVs) such as deletions, inversions, and translocations, impact more nucleotides per human genome than any other form of genetic variation. They are major contributors to genetic diversity and disease but studying their impact in an unbiased manner in high throughput has been difficult. In particular, we have lacked efficient methods to generate, track, and analyze SVs in mammalian cell models.
How did you go about solving this problem?
We developed Genome-Shuffle-seq, a technique that uses barcoded “shuffle cassettes” that contain recognition sites for site-specific recombinases like Cre. To enable large-scale SV generation, we randomly integrated these cassettes into mammalian genomes using a transposon system and mapped their locations by associating the barcodes found on each cassette with their integration sites in the genome. When the recombinase is introduced, shuffle cassettes recombine with each other, leading to rearrangements such as deletions, inversions, and translocations. This process alters the barcode pairs present on the same DNA molecule, which we can track through high-throughput sequencing. By sequencing these barcode pairs in bulk populations or at the single-cell level, we can precisely map SV breakpoints and assess their impact on gene expression and cellular fitness.
How would you explain your research outcomes (Key findings) to the non-scientific community?
Imagine that our genome is like a book, where the order of pages matters. If the pages get shuffled randomly, some changes might leave the story intact, while others could remove key chapters, altering the meaning entirely. In the same way, structural variants (SVs) – large genomic rearrangements like deletions, inversions, and translocations – occur naturally in human populations and diseases, but we don’t fully understand their effects. Our method, Genome-Shuffle-seq, allows us to intentionally “shuffle” pages in the genome in a controlled way and observe the consequences. By tracking these changes in cells, we can determine which rearrangements are harmful, which are neutral, and how cells adapt to them over time. This helps us uncover how genomic structure contributes to function, evolution, and disease, bringing us closer to understanding the rules that govern genome organization.
What are the potential implications of your findings for the field and society? We believe that our method will advance our understanding of how SVs impact disease progression, the fundamental principles of genome structure, and guide the engineering of mammalian genomes. In the context of genetic diseases, our approach can help uncover how large-scale mutations in the genome contribute to conditions like cancer. By introducing and tracking structural changes in a controlled way, we can begin to understand which rearrangements drive disease and which ones cells can tolerate. SVs have played an important role in shaping evolution and speciation. We hope that by creating cells with altered genomes, we can understand the constraints on genome organization. Finally, this research could be used to design more efficient, streamlined mammalian genomes, identifying which genetic elements are essential and which can be altered without disrupting function. This could have applications in biotechnology, bioengineering, and even the development of future cell and gene therapies.
What was the most exciting moment during your research?
The most exciting moment was when we had the first proof-of-concept data showing that the scheme that we had drawn out on paper was working as intended. One of the most rewarding parts of technology development research is watching an idea move from a concept to something that works in practice.
Genome-Shuffle-seq enables the generation and characterization of thousands of structural variants (SVs) in mammalian genomes, even at single-cell resolution. Recombination events create novel barcode combinations, allowing high-throughput tracking of SVs.
Reference: Sudarshan Pinglay et al., Science 387, eado5978 (2025). DOI: 10.1126/science.ado5978
