Single-Cell Genetic Screening Using Virtual Reads and Parental Data
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Solution Overview
Problem
Current pre-implantation genetic diagnosis (PGD) techniques for IVF are unreliable, expensive, and inefficient in accurately determining genetic data from a single cell, particularly in screening for aneuploidy and disease-linked loci, leading to high error rates and increased costs, which complicates the selection of healthy embryos for implantation.
Innovation Solution
A method that involves obtaining cells from embryos, determining specific characteristics, and estimating the likelihood of successful development by predicting genetic probabilities, allowing for the ranking and selection of embryos based on their potential to result in healthy babies, using mathematical correlations and secondary genetic data to improve accuracy and reduce noise in genetic measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current PGD techniques are used to screen single cells for aneuploidy and disease-linked loci, then genetic screening can be performed, but error rates increase to approximately 10% due to noisy measurements from single cell DNA
Solution Approach 1:
The patent creates virtual copies of the single cell's genetic data by generating multiple simulated sequencing reads from the limited physical DNA. These virtual copies allow statistical analysis and error correction without requiring additional physical cells, thereby improving measurement precision while maintaining the single-cell basis of the assay.
Solution Approach 2:
The patent introduces secondary genetic data from related individuals (parents, siblings) as an intermediary to infer and correct the primary genetic measurements from the single cell. This intermediary data serves as a reference to identify and correct measurement errors, improving the reliability of the screening without directly measuring the single cell again.
2Adaptability or versatility
If multiple genetic markers are screened in parallel for aneuploidy and monogenic diseases, then comprehensive genetic screening is achieved, but the complexity and cost of testing increases
Solution Approach 1:
The patent creates a universal analytical framework that can simultaneously detect multiple types of genetic abnormalities (aneuploidy, monogenic diseases, complex disease susceptibility) using the same single-cell DNA sample and statistical methods. This multi-functional approach eliminates the need for separate testing protocols for different disease types, reducing overall complexity while maintaining comprehensive screening capability.
Solution Approach 2:
The patent merges the analysis of multiple genetic markers and multiple disease types into a single integrated statistical framework. By combining the evaluation of aneuploidy, monogenic diseases, and complex disease susceptibility markers in one unified analysis pipeline, the patent reduces the operational complexity and cost compared to performing separate specialized tests for each condition.
3Measurement precision
If direct measurements of single cell DNA are performed, then genetic data can be obtained, but the measurements are highly error-prone and noisy
Solution Approach 1:
The patent implements feedback mechanisms where the statistical model continuously refines its predictions by comparing expected genetic patterns against observed data. The model uses feedback from secondary genetic data and from comparing multiple virtual reads to correct individual measurement errors, thereby improving the reliability of the final genetic calls without requiring perfectly precise direct measurements.
Solution Approach 2:
The patent performs preliminary actions by generating multiple virtual sequencing reads from the limited physical DNA before actual analysis. These pre-simulated reads allow the system to establish expected signal patterns and statistical distributions in advance, enabling more reliable detection and correction of measurement errors during the actual genetic screening process.
Data Source
AI summary
Disclosed herein is a system and method for making allele calls, and for determining the ploidy state, in one or a small set of cells, or where a limited quantity of genetic data is available. Poorly or incorrectly measured base pairs, missing alleles and missing regions are reconstructed and the haplotypes are determined using expected similarities between the target genome and the knowledge of the genomes of genetically related individuals. In one embodiment, incomplete genetic data from an embryonic cell are reconstructed at a plurality of loci using the genetic data from both parents, and possibly one or more sperm and/or sibling embryos. In another embodiment, the chromosome copy number can be determined using the same input data. In another embodiment, these determinations are made for embryo selection during IVF, for non-invasive prenatal diagnosis, or for making phenotypic predictions.