SNP Microarray Probes for Functional Variant Identification
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Solution Overview
Problem
Current technologies lack the capability to effectively identify and differentiate functional single nucleotide polymorphisms (SNPs) associated with diseases, particularly in complex genetic disorders like prostate cancer, which hinders personalized medicine approaches.
Innovation Solution
A high-throughput microarray technology is developed to evaluate SNP function by using probes representing 25-base pair regions of the genome with SNPs, allowing for the simultaneous testing of millions of SNPs and transcription factor interactions, thereby identifying functional SNPs associated with diseases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If high-throughput microarray technology is used to evaluate millions of SNPs simultaneously, then productivity in identifying functional SNPs is improved, but device complexity increases
Solution Approach 1:
The microarray system divides the genome into discrete 25-base pair probe regions, each representing specific SNP alleles. This segmentation allows millions of SNPs to be evaluated simultaneously through parallel processing of individual probe features on the microarray substrate.
Solution Approach 2:
The microarray platform serves multiple functions: it stores genomic probe sequences, enables transcription factor binding assays, provides fluorescent detection capabilities, and facilitates high-throughput data collection. This multi-functionality consolidates what would otherwise require separate systems into a single integrated platform.
2Measurement precision
If detailed functional analysis of each SNP is performed to identify causative variants, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system pre-positions fluorescent labels on transcription factors before they contact the microarray. This preliminary action enables simultaneous detection of multiple binding events across all probes during a single hybridization event, eliminating sequential analysis time while maintaining functional precision.
Solution Approach 2:
The microarray creates physical copies of genomic probe sequences (25-base pair regions) representing different SNP alleles. These copied probe sequences are arrayed in parallel, allowing functional equivalence testing of millions of SNPs simultaneously rather than analyzing each individually over time.
3Reliability
If comprehensive genomic regions are analyzed to identify disease-associated SNPs, then reliability of disease association is improved, but quantity of substance (DNA material) required increases
Solution Approach 1:
The system focuses analysis on specific 25-base pair local regions containing SNP alleles rather than analyzing entire genomes uniformly. This localized approach concentrates DNA material usage on functionally relevant segments while maintaining reliability through comprehensive coverage of disease-associated genomic regions.
Solution Approach 2:
The microarray uses synthetic oligonucleotide probes (25 bases) that are chemically synthesized rather than extracted from biological sources. These short synthetic DNA molecules are inexpensive to produce in large quantities and can be reused across multiple experiments, reducing both material cost and quantity requirements compared to traditional genomic DNA approaches.
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 technology enables the identification of causative SNPs in diseases like prostate cancer, providing a molecular signature for disease prediction and treatment strategies, and is broadly applicable to various diseases and models.
Implementation Method 1
Each probe on the microarray is displayed as double-stranded DNA matching a 25 base pair (bp) region of the genome comprising a SNP allele
Implementation Method 2
a key under-studied function of SNPs is their ability to generate or disrupt genomic binding sites for biomolecules (e.g., proteins, metabolites, nucleic acids) that modulate gene expression, such as transcription factors involved in a disease
Data Source
AI summary
Provided herein is technology relating to genetic determinants of disease and particularly, but not exclusively, to methods, compositions, and systems for identifying single nucleotide polymorphisms that are functionally associated with a disease.