Does a giraffe need a telomere-to-telomere diploid genome assembly?

Thursday, 3 September 2026, 10am to 11am

For our BDI Distinguished Seminar, we will hear from Professor Pavel Pevzner, Ronald R. Taylor Chair and Distinguished Professor of Computer Science and Engineering at the University of California, San Diego, on Thursday 3 September, 10:00 am – 11:00 am, at the Big Data Institute (BDI).

Title: Does a giraffe need a telomere-to-telomere diploid genome assembly?

Date: Thursday 3 September
Time: 10:00 am - 11:00 am
Venue: BDI/OxPop, Seminar Room 0; followed by refreshments in the atrium

Abstract:
Recent telomere-to-telomere (T2T) sequencing projects have transformed genomics by delivering near-complete diploid assemblies that reconstruct both haplomes. However, attaining this gold standard remains labor-intensive, requiring multiple sequencing technologies, manual curation, and a level of dedication that occasionally borders on obsession.
Fortunately, biologists often do not need a gold-plated diploid genome to study their favorite species. For many applications, a near-complete haplotype-mixed (HM) assembly—a “virtual child” genome representing a mosaic of the two haplomes—captures most of the information required for downstream analyses while avoiding much of the cost and complexity of diploid assembly. In principle, HM assemblies can be generated automatically and inexpensively using a single sequencing technology (e.g., long and accurate HiFi or ONT reads). In practice, however, existing HM assemblers still struggle to generate near-complete assemblies.
We present the Mosaic Genome Assembler (MGA), which constructs near-complete HM assemblies from a single sequencing technology. Benchmarking across diverse genomes shows that MGA substantially outperforms existing haplotype-mixed assemblers while eliminating the need for additional sequencing technologies. MGA does not replace T2T diploid assemblies; rather, it offers a pragmatic alternative for the many projects that need a high-quality “virtual child” reference genome, but not necessarily Mom and Dad genomes.
About the speaker:
Pavel Pevzner is the Ronald R. Taylor Chair and Distinguished Professor of Computer Science and Engineering at the University of California, San Diego. He received his Ph.D. from Moscow Institute of Physics and Technology, Russia. Dr. Pevzner was named a Howard Hughes Medical Institute Professor in 2006 and has received various accolades, including election as a Fellow of the Association for Computing Machinery (2010), the International Society for Computational Biology (2012), the Academia Europaea (2016), and the American Association for the Advancement of Science (2018). He has received honorary doctorates from Simon Fraser University (2011) and Tel Aviv University (2023), the Senior Scientist Award from the International Society for Computational Biology (2017), and the Kanellakis Theory and Practice Award from the Association for Computing Machinery (2019). Dr. Pevzner authored textbooks "Computational Molecular Biology: An Algorithmic Approach", "Introduction to Bioinformatics Algorithms" (with Neal Jones), “Bioinformatics Algorithms: an Active Learning Approach” (with Phillip Compeau), and “Learning Algorithms through Programming and Puzzle Solving” (with Alexander Kulikov). He also co-developed the Coursera online specializations in Bioinformatics and Algorithms, which have collectively attracted over 700,000 learners worldwide.

Speaker(s): Prof Pavel Pevzner (University of California at San Diego (UCSD))

Series: BDI Distinguished Seminar

Venue: Big Data Institute - Lower Ground Seminar Room 0 - Lower Ground Seminar Room 0 Big Data Institute Old Road Campus Oxford Oxfordshire OX3 7LF United Kingdom

Department: Big Data Institute - NDPH (Unit)

Organiser: Sumeeta Maheshwari

Host: Prof Trey Ideker

More info: