High Throughput Hla Sequence-Based Typing (Sbt) Utilizing the Abi Prism® 3700 Dna Analyzer

2001 ◽  
Vol 87 (2) ◽  
pp. 40-43 ◽  
Author(s):  
Sharon D Adams ◽  
Kathleen C Barracchini ◽  
Toni B Simonis ◽  
David Stroncek ◽  
Francesco M Marincola

Aims and background The genetic complexity of the human major histocompatibility complex (MHC) has required the development of various molecular typing methods. The purpose of this paper is to compare the results of two of these molecular methods: sequenced based typing (SBT) and polymerase chain reaction (PCR) using sequence specific primers (PCR-SSP). Methods The SBT method described utilizes an ABI Prism® 3700 DNA Analyzer, which has been designed fro high throughput production of sequence data through highly automated operation with significant walk-away time. The ABI Prism® 3700 DNA Analyzer is a 96-capillary electrophoresis instrument with the capability of running four 96-well plates black to back in a sixteen-hour period. Potentially, data from this machine can produce Class I sequences for A or B loci for 64 samples in this time frame. The SBT method encompassed exons 2, 3, and 4 with forward and reverse sequence orientation reactions using the PE Biosystems HLA-A and HLA-B Sequenced Based Typing Kits (PE Applied Biopsystems/Perkin-Elmer, Foster City, CA, USA). Most SBT methods previously employed only gather data from exons 2 and 3 which distinguishes most of the polymorphism necessary to identify the majority of alleles in the HLA region. However, in an effort to discern numerous null alleles in the HLA region, exon 4 data is also included. The PCR-SSP method utilized consists of one 96 well tray, with 95 primer mixes and one negative control, per sample designed to produce an intermediate/high resolution HLA-A, B typing. Results Data from one 96-well capillary run on the ABI Prism® 3700 DNA Analyzer, which consists of results from 16 samples for HLA-A or HLA-B loci, was compared to data derived from sixteen HLA-A and HLA-B PCR-SSP typings. 75% of loci tested achieved a higher resolution HLA typing by the SBT method. Discussion The ability to provide allele level HLA typing results can have significant functional implications for the bone marrow transplant community and numerous vaccine studies.

2015 ◽  
Vol 76 ◽  
pp. 162
Author(s):  
Helen LaCarrubba ◽  
Zachary Antovich ◽  
Komal Singh ◽  
Dennis Miguel ◽  
Patty Harris Bowe ◽  
...  

1999 ◽  
Vol 20 (11) ◽  
pp. 756-758 ◽  
Author(s):  
Jeffrey D. Klausner ◽  
Carol Zukerman ◽  
Ajit P. Limaye ◽  
Lawrence Corey

AbstractUsing molecular typing methods, we confirmed an outbreak ofStenotrophomonas maltophiliaamong bone marrow transplant patients. The likely source was a healthcare worker who may have washed with moisturizer instead of soap between patients. Hospital epidemiologists need to go beyond antibiograms when evaluating outbreaks and be vigilant about all aspects of hand washing.


2009 ◽  
Vol 25 (19) ◽  
pp. 2607-2608 ◽  
Author(s):  
M. Morgan ◽  
S. Anders ◽  
M. Lawrence ◽  
P. Aboyoun ◽  
H. Pages ◽  
...  

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Sanghoon Kang ◽  
Jorge L. M. Rodrigues ◽  
Justin P. Ng ◽  
Terry J. Gentry

2014 ◽  
Vol 490-491 ◽  
pp. 757-762
Author(s):  
Guo Li Ji ◽  
Long Teng Chen ◽  
Liang Liang Chen

This paper proposed a way of two-level parallel alignment based on sequence parallel vectorization with GPU acceleration on the Fermi architecture, which integrates sequence parallel vectorization, parallel k-means clustering approximate alignment and parallel Smith-Waterman algorithm. The method converts sequence alignment into vector alignment by first. Then it uses k-means alignment to divide sequences into several groups and reduce the size of sequence data. The expected accurate alignment result is achieved using parallel Smith-Waterman algorithm. The high-throughput mouse T-cell receptor (TCR) sequences were used to validate the proposed method. Under the same hardware condition, comparing to serial Smith-Waterman algorithm and CUDASW++2.0 algorithm, our method is the most efficient alignment algorithm with high alignment accuracy.


2010 ◽  
pp. 367-379
Author(s):  
Raja Rajalingam ◽  
Michael Cecka ◽  
Elaine F. Reed

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