Descriptive Title of Project:
Application of Long-Read Genome Sequencing to Improve Rare Disease Diagnosis and Discovery in Pediatric Cohorts
Research Use Statement:
Rare diseases affect millions of children worldwide, yet a substantial proportion of patients remain without a molecular diagnosis despite extensive clinical evaluation and short-read genomic sequencing. Many unresolved cases are believed to be attributable to structural variants, repeat expansions, methylation abnormalities, complex genomic rearrangements, and variants located within repetitive or difficult-to-sequence regions of the genome.
Recent advances in long-read sequencing technologies, including Pacific Biosciences (PacBio) HiFi sequencing and Oxford Nanopore Technologies (ONT), have demonstrated the ability to resolve complex genomic variation that is difficult to detect using traditional short-read approaches. Long-read sequencing enables improved detection of structural variants, copy number variants, tandem repeat expansions, phasing of compound heterozygous variants, breakpoint resolution, methylation profiling, and characterization of complex chromosomal rearrangements.
In this project, we will leverage long-read sequencing datasets and associated phenotypic information available through the Kids First Data Resource Center to investigate the contribution of structural and complex genomic variation to pediatric rare diseases. We will apply established long-read analytical pipelines, including structural variant detection, small variant calling, copy number analysis, tandem repeat genotyping, methylation analysis, and variant annotation workflows. Candidate pathogenic variants will be prioritized using population allele frequencies, functional annotations, inheritance patterns, and clinical phenotype information.
This work is part of the collaborative Kids First Long Reads Working Group, a multi-institution group of investigators looking to improve understanding of the genetic architecture of rare pediatric diseases and help identify novel disease-causing variants, genes, and mechanisms. Work on this project will utilize cloud-based computational infrastructure on the Terra and/or CAVATICA platforms and standardized long-read analysis pipelines to process genomic data and integrate findings with available clinical and phenotypic information.
Non-Technical Summary:
Many children with rare diseases undergo extensive genetic testing but still do not receive a diagnosis. Traditional DNA sequencing technologies can miss important genetic changes, particularly large rearrangements, repeat expansions, and other complex variants. Long-read sequencing provides a more complete view of the genome and can reveal disease-causing genetic changes that were previously undetectable.
This project will analyze long-read genomic data from pediatric rare disease cohorts to identify genetic causes of disease, improve diagnostic rates, and better understand the biological mechanisms underlying rare disorders. Findings from this work may improve future diagnostic approaches and accelerate gene discovery efforts for children and families affected by rare diseases.
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