HLA Haplotyping via Long-Range PCR and CSA Algorithm
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Solution Overview
Problem
Current HLA typing methods, such as serological and DNA sequencing, face challenges in accurately determining haplotypes due to high error rates, variability, and incomplete data from targeting only exons, which is insufficient for definitive haplotype determination and histocompatibility matching in transplantation and disease susceptibility analysis.
Innovation Solution
The method involves amplifying entire HLA genes using long-range PCR, deep sequencing, and deconvolution analysis with the Chromatid Sequence Alignment (CSA) algorithm to resolve haplotypes, providing linkage information between exons and accurate haplotype determination by sequencing both intron and exon regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional DNA sequencing approaches target only exons, then sequencing cost and complexity are reduced, but haplotype determination accuracy is insufficient due to lack of linkage information
Solution Approach 1:
The HLA gene is divided into multiple exons that are sequenced separately and then assembled using the CSA algorithm to reconstruct the complete haplotype sequence, resolving phase ambiguity by linking exon sequences
Solution Approach 2:
The Chromatid Sequence Alignment (CSA) algorithm serves as an intermediary computational tool that integrates sequencing data from multiple exons and determines the phase relationship between alleles, enabling accurate haplotype reconstruction without direct long-range sequencing
2Reliability
If serological typing methods are used, then the process is simpler and faster, but error rate and variability increase due to alloantisera availability and crossreactivity issues
Solution Approach 1:
The patent replaces serological methods (which rely on antibody-antigen interactions and manual interpretation) with DNA-based molecular methods that use automated sequencing and computational analysis, eliminating crossreactivity issues and improving reproducibility
3Measurement precision
If fragmental exon sequencing is performed, then sequencing depth is sufficient for individual exons, but incomplete data is generated that is not sufficient for definitive haplotype determination
Solution Approach 1:
The CSA algorithm uses feedback from sequencing depth and quality metrics across multiple exons to iteratively improve haplotype reconstruction accuracy, ensuring sufficient coverage while maintaining cost-effectiveness
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides accurate and comprehensive HLA haplotyping, reducing errors and variability, and enabling precise matching in transplantation and disease association studies, with the ability to discover novel alleles and improve resolution of genetic differences.
Implementation Method 1
amplifying an entire HLA gene using long-range PCR
Data Source
AI summary
Methods are provided to determine the entire genomic region of a particular HLA locus including both intron and exons. The resultant consensus sequences provides linkage information between different exons, and produces the unique sequence from each of the two genes from the individual sample being typed. The sequence information in intron regions along with the exon sequences provides an accurate HLA haplotype.