Progress in detecting genetic alterations and their association with human disease

Area of Science:

• Genomics and Genetic Medicine
• Molecular Biology and Bioinformatics

Background:

• The Human Genome Project provided a reference genome for identifying disease-causing mutations.
• Early methods like Sanger sequencing were time-consuming and limited in scope for large-scale genetic screening.

Purpose of the Study:

• To highlight the evolution of genetic sequencing technologies for disease mutation identification.
• To underscore the current challenges in analyzing massive datasets generated by next-generation sequencing.

Main Methods:

• Review of historical and current genetic sequencing methodologies, from Sanger sequencing to next-generation sequencing (NGS).
• Discussion of the technological advancements enabling whole exome sequencing of multiple individuals.

Main Results:

• Next-generation sequencing significantly reduced the time required for exome sequencing (approximately 10 days).
• The massive data output from NGS presents a significant bottleneck in identifying relevant genetic alterations.

Conclusions:

• While NGS has revolutionized the speed of genetic data generation, data filtering and analysis are critical rate-limiting steps.
• Efficient bioinformatics pipelines are essential for translating vast genomic data into clinically relevant findings for human disorders.