Phasing and Linking Long Fragment Reads for Genomic Variation Detection
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Solution Overview
Problem
Current pre-implantation genetic diagnosis (PGD) methods for in vitro fertilization (IVF) are inadequate in detecting de novo mutations and variations not associated with specific diseases, missing many genomic defects and failing to improve the health of IVF newborns, as they primarily focus on large genomic alterations or single-gene disorders.
Innovation Solution
The implementation of phasing and linking processes using long fragment reads (LFR) to identify haplotypes and resolve base calls, allowing for the accurate detection of hemizygous deletions, insertions, and other variations by utilizing shared labels and phasing rates, thereby improving the identification of genomic defects in embryos.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current PGD methods are used to detect large genomic alterations or single-gene disorders, then the diagnostic process is simple and fast, but many genomic defects including de novo mutations are missed
Solution Approach 1:
The diagnostic process is segmented into multiple stages: initial screening for large genomic alterations, followed by whole genome sequencing for comprehensive variant detection, and finally bioinformatic analysis to identify de novo mutations. This segmentation allows the system to achieve high detection accuracy while managing complexity through structured workflow
Solution Approach 2:
The method performs preliminary whole genome sequencing and bioinformatic filtering to identify potential de novo mutations before final diagnostic confirmation. This preliminary action enables the detection of previously undetectable variants while maintaining diagnostic efficiency through pre-screening
2Reliability
If comprehensive whole genome sequencing is performed to detect all genomic variations, then detection accuracy improves, but the cost and time required increase significantly
Solution Approach 1:
The system performs preliminary bioinformatic filtering to identify de novo mutations and high-priority variants before comprehensive diagnostic analysis. This preliminary action reduces the time required by focusing subsequent detailed analysis only on relevant findings rather than processing all genomic data equally
Solution Approach 2:
The diagnostic process incorporates feedback loops where initial sequencing results guide subsequent analysis priorities. If de novo mutations are detected, the system automatically prioritizes further investigation of those specific variants, reducing overall diagnostic time while maintaining comprehensive coverage
3Reliability
If current PGD methods are used, then the process is cost-effective, but the ability to identify de novo mutations and improve IVF newborn health is limited
Solution Approach 1:
The system performs preliminary identification of de novo mutations through bioinformatic analysis of whole genome sequencing data. This preliminary action enables targeted intervention only when necessary, improving health outcomes while avoiding unnecessary resource consumption in cases where no de novo mutations are present
Solution Approach 2:
The diagnostic approach changes parameters by transitioning from targeted analysis of specific genes to comprehensive whole genome sequencing. This parameter change enables detection of any genomic variation including de novo mutations, thereby improving health outcome prediction while the bioinformatic filtering manages resource requirements
Data Source
AI summary
Long fragment read techniques can be used to identify deletions and resolve base calls by utilizing shared labels (e.g., shared aliquots) of a read with any reads corresponding to heterozygous loci (hets) of a haplotype. For example, the linking of a locus to a haplotype of multiple hets can increase the reads available at the locus for determining a base call for a particular haplotype. For a hemizygous deletion, a region can be linked to one or more hets, and the labels for a particular haplotype can be used to identify which reads in the region correspond to which haplotype. In this manner, since the reads for a particular haplotype can be identified, a hemizygous deletion can be determined. Further, a phasing rate of pulses can be used to identify large deletions. A deletion can be identified with the phasing rate is sufficiently low, and other criteria can be used.