High-Throughput Sequencing of T-Cell Receptors


To scale up a high-throughput T cell receptor gene sequencing service to expand researcher access and enable better diagnostics and treatments for conditions involving the immune system

Anticipated Impact: 

Enhanced competitiveness of the collaborating in-state company and the broader immunology research community, which may improve the diagnosis and treatment of immune-related conditions


T cell receptors (TCRs) are key components of the immune system and are also believed to play a role in autoimmune disease. Dr. Robins and colleagues have developed a method to sequence TCR genes at very high throughput and formed a company, Adaptive TCR Corporation, to offer this service to the research community. TCR sequence information allows investigators to study topics such as immune system reconstitution following cord blood transplantation; immune responses to vaccines; and association of specific TCRs with autoimmune disorders. The proposed work will scale up Adaptive TCR's sequencing service by improving the assay as well as the associated software/analytical tools. This scale-up is anticipated to markedly reduce the cost of Adaptive TCR's service and thus broaden researcher access within a short timeframe. In addition to enhancing research competitiveness, this expanded access could potentially enable improved post-transplantation treatment protocols, more effective vaccines, and new diagnostics for autoimmune disorders.

See also:

T Cell Receptor Sequencing

Grant Update

Principal Investigator:
Harlan Robins
Grantee Organization:
Fred Hutchinson Cancer Research Center
Grant Title:
High-Throughput Sequencing of T-Cell Receptors
Grant Cohort and Year:
2010 First Round Commercialization (03)
Grant Period:
10/10/2010 - 10/09/2011 (Completed)
Grant Amount:
We have developed and tested 12 bar-codes for our T cell receptor beta (TCRB) sequencing assay. Despite initial delays due to machinery problems, our progress was quite smooth. The bar codes are read out as a second read from the same cluster on the Illumina chip as the TCRB sequence. Between 0.1 and 1% levels, the Illumina imaging software makes a mistake and matches (the incorrect) read-1 (the TCRB) to read-2 (the bar code). This appears as low level contamination in our data (mixing of bar coded samples on the same lane). In order to offer this service commercially, this mixing is unacceptable. After working with Illumina, they agreed to test this by bar coding a human sample and a bacteria sample and putting them in the same lane. Fortunately, they yielded similar results. They observed a low level of mixing between human and bacteria. We also attempted a variety of methods to work around their mixing error. We were able to find a solution that works very well, but with some significant drawbacks. For our read-2, instead of stopping after our 8-base bar code, we continue to sequence through 60 nucleotides. Then we align read 1 and read 2. If they do not align, this means that read-2 and read-1 do not match. When we throw out these sequences, the mixing problem disappears. Unfortunately, the drawback is that each run spends more time on the sequencer and burns more reagents. In addition, we have rewritten the software for our processing pipeline, which is now much faster and producing far less noise. This software is in our regular production pipeline. For TCRB, everything is working fine now and has been thoroughly tested. We have also bar-coded TCRG and this works fine as well. We are now in the process of bar coding our IgH assay, which has its own difficulties, and is outside the scope of this grant.

Impact in Washington

Location of LSDF Grantee
Locations of Collaborations/Areas of Impact

Legislative Districts:
11, 34, 36, 37, 43, 46

Health Impacts

T Cell Receptor Sequencing