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Economical high throughput de novo whole genome assembly

Status: 
Active
Competition: 
2015 Disruptive Innovation in Genomics Competition
Sector: 
Health
Genome Centre(s):
Ontario Genomics
Project Leader(s):
Stephen Scherer (The Hospital for Sick Children (SickKids)), Si Lok (The Hospital for Sick Children (SickKids))
GE3LS: 
No
Fiscal Year Project Launched: 
2016-2017
Project Description: 

Phase 1 Project

Whole genome sequencing is a prerequisite for precision medicine targeted to the specific needs of a unique individual. Currently, however, the common practice is “re-sequencing” – comparing an individual’s genome to a reference genome and noting the differences. This process, though, can miss up to half the causal mutations for disease. The alternative – “de novo” sequencing, or constructing an individual’s genome from his or her own data alone – is a formidable task, akin to assembling a jigsaw puzzle comprising hundreds of millions of small blank pieces based on their shapes alone. Moreover, many pieces would have identical shapes, corresponding to repeated regions of the genome. This makes the financial and logistical costs of de novo sequencing impractical, if not impossible, for routine use.

Drs. Si Lok, Stephen Scherer, and their colleagues from The Hospital for Sick Children are developing a new “mate-pair” technology, in which each sequence read is unambiguously linked to one or more other reads in precisely known orientations and distances. In the jigsaw puzzle analogy, this information would allow placement of multiple puzzle pieces in respect to others without the need of physical contact. Mate-pair technology would interconnect the genome to create a high-resolution backbone to enable de novo sequencing to be carried out in a single simple step, removing both the financial and logistical barriers. This new adaptation of mate-pair sequencing is a disruptive technology that could supersede essentially all current methods for de novo sequencing, thereby representing a leap forward in how genomics is used in many areas of research, and ultimately in healthcare.