About Us

We are the Genomics Research to Elucidate the Genetics of Rare disease (GREGoR) Consortium Stanford Site.

Our goal is to provide a platform for functional genomics research and validation to improve diagnosis in Mendelian disease. We believe that the systematic application of promising new genomics technologies coupled with innovative computational approaches will foster discovery. Research participants who remain undiagnosed after exome sequencing will undergo short read and long read genome sequencing, transcriptome sequencing, methylation assays, metabolomics and/or lipidomics assays. Novel causal variants and genes will be validated through state-of-the-art targeted approaches including massively parallel reporter assays, induced-pluripotent stem cell assays and CRISPR engineered cellular and mouse models. Our approach will help elucidate the most effective ‘omics’ strategies to improve Mendelian disease discovery and diagnosis.

Why GREGoR?

Our name is inspired by Gregor Johann Mendel. Gregor Mendel was an Austrian monk who through a series of pea plant experiments performed in the 19th century established many of the rules of heredity, now referred to as the laws of Mendelian inheritance.

What do we aim to do at GREGoR Stanford Site?

Enhance emerging paradigms for Mendelian Genomics

At GREGoR Stanford Site our goal is to comprehensively study ‘exome-negative’ individuals with undiagnosed Mendelian disease. Samples from research participants and their immediate family members may undergo:

Short and long-read genome sequencing
Metabolomic and/or lipidomics profiling
RNA-sequencing
ATAC-sequencing
Methyl-capture-sequencing

When available these assays will be performed across multiple commonly accessed cell/tissue types. These assays will be compared against large sets of genomic and functional genomic controls to detect aberrant gene or variant signatures.

Develop new computational strategies for gene and variant prioritization

We will develop and expand methods to:

Automate phenotype-gene-literature data integration
Detect aberrant gene signatures using multi-omics and family data
Integrate case-specific omics for variant effect prediction
Integrate polygenic risk profiles to estimate genetic background effects
Predict informative assays based on existing casa data to determine strategic application of multi-omics technologies

All new approaches will be extensively documented to enable broad integration and extension.

Employ targeted experimental approaches to identify causal genes and variants

We will utilize high-throughput and targeted approaches to enhance and evaluate causal genes and variants in selected cases including:

Massively parallel reporter assays (MPRA)
Targeted CRISPR for rare variant interpretation
High-throughput CRISPR reporter gene screens
iPSC functional genomics
CRISPRi mouse models