Single-Cell Haplotyping via MDA and SNP Arrays
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Solution Overview
Problem
Current genotyping and haplotyping methods face challenges when analyzing single or few cells due to errors from whole genome amplification artifacts, such as allele dropout and preferential amplification, leading to false haplotype estimations and misdiagnosis in applications like preimplantation genetic diagnosis and genetic studies of heterogeneous tissues.
Innovation Solution
The method involves picking a single or dual cell, lysing and amplifying DNA using multiple displacement amplification, followed by massively parallel genetic polymorphism typing on an Affymetrix SNP-array, and using algorithms like the Dynamic Model and MERLIN for haplotype reconstruction, with optional steps for selecting heterozygous SNPs and generating virtual genotypes to correct allelic allocations and reduce noise through smoothing techniques like the 1D median filter.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If whole genome amplification is performed on single cells, then sufficient DNA for analysis is obtained, but amplification artifacts such as allele dropout and preferential amplification occur leading to genotyping errors
Solution Approach 1:
The genome is divided into multiple independent amplification reactions targeting specific chromosomal regions rather than attempting to amplify the entire genome in a single reaction. This segmentation reduces the complexity of each amplification reaction, minimizing allele dropout and preferential amplification artifacts while still generating sufficient DNA for genotyping when combined across multiple reactions
Solution Approach 2:
Statistical models and computational algorithms serve as intermediaries between the amplified DNA products and the final genotype calls. These algorithms account for and correct amplification biases by analyzing patterns across multiple loci and reactions, transforming noisy raw data into reliable genotype information
2Loss of information
If multiple polymorphic markers are analyzed genome-wide, then comprehensive haplotype information is obtained, but the complexity of data analysis and interpretation increases significantly
Solution Approach 1:
The method performs preliminary statistical analysis during the genotyping phase itself, using the same data to both call genotypes and estimate haplotypes simultaneously. This integrated approach avoids the need for separate, complex haplotype reconstruction steps and reduces overall analytical complexity while maintaining comprehensive haplotype information
Solution Approach 2:
The methodology transforms the problem from direct haplotype reconstruction to probabilistic genotype likelihood estimation, changing the analytical parameters from deterministic to statistical. This parameter transformation simplifies the mathematical framework and enables efficient computation even with genome-wide marker data
3Loss of information
If single cell analysis is performed to study heterogeneous tissues, then cell-specific genetic information is obtained, but amplification errors and noise reduce the quality of genetic polymorphism typing
Solution Approach 1:
The system uses feedback from multiple independent genetic markers to validate and correct calls at individual loci. By analyzing the consistency of inheritance patterns across the genome, the method identifies and corrects erroneous calls resulting from amplification errors, thereby maintaining high typing accuracy in single-cell analyses
Solution Approach 2:
The methodology creates multiple independent copies of the genetic information through analysis of multiple polymorphic markers distributed across the genome. This redundant sampling approach allows statistical validation of genotype calls and filtering of spurious signals caused by amplification artifacts
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 enables accurate genome-wide haplotyping of single cells, reducing errors and improving the interpretation of haplotypes, thereby enhancing the reliability of genetic analysis and embryo selection in preimplantation genetic diagnosis and other applications by correcting for amplification artifacts and false allelic assignments.
Implementation Method 1
amplifying DNA using multiple displacement amplification
Data Source
AI summary
We developed a generic approach to type genome-wide single nucleotide polymorphisms in single human cells and to reconstruct for the first time genome-wide haplotypes of single- or dual-cell derived genotypes. Proof-of-principle is delivered for EBV-transformed lymphoblastoid cells as well as human blastomeres. To this end, multiple displacement amplified DNA samples of single cells were hybridized to Affymetrix 250K SNP-arrays. Different algorithmic designs were subsequently developed to assess from the single-cell derived SNP-probe intensities the sequence of syntenic alleles and to pinpoint accurately the majority of parental homologous recombination sites across the entire genome using a linkage-based approach. This included the development of algorithms that rectify a large part of the discrepant allelic assignments in raw single or dual-cell derived haplotypes. This method to infer genome-wide haplotypes from the analysis of only one or two cells has tremendous applicative value. It has the capacity to revolutionize not only genetic diagnosis of preimplantation in vitro fertilized human embryos in the clinic, but also animal breeding programs by enabling genome-wide quantitative trait loci selection at the embryonic level. In addition, it allows to further scrutinize drivers of haplotype diversity, mainly meiotic homologous recombination as well as somatic (homologous) recombination processes that occur often during (human) tumorigenesis.