Project description:Studying the functional consequences of structural variants (SVs) in mammalian genomes is challenging because: 1) SVs arise much less commonly than single nucleotide variants or small indels; and 2) methods to generate, map and characterize SVs in model systems are underdeveloped. To address these challenges, we developed Genome-Shuffle-seq, a method that enables the multiplex generation and mapping of thousands of SVs (deletions, inversions, translocations, extrachromosomal circles) throughout mammalian genomes. We also demonstrate the co-capture of SV identity with single-cell transcriptomes, facilitating the measurement of SVs’ impact on gene expression. We anticipate Genome-Shuffle-seq will be broadly useful for the systematic exploration of the functional consequences of SVs on gene expression, chromatin landscape, and 3D nuclear architecture, while also initiating a path towards a minimal mammalian genome.
Project description:Studying the functional consequences of structural variants (SVs) in mammalian genomes is challenging because: 1) SVs arise much less commonly than single nucleotide variants or small indels; and 2) methods to generate, map and characterize SVs in model systems are underdeveloped. To address these challenges, we developed Genome-Shuffle-seq, a method that enables the multiplex generation and mapping of thousands of SVs (deletions, inversions, translocations, extrachromosomal circles) throughout mammalian genomes. We also demonstrate the co-capture of SV identity with single-cell transcriptomes, facilitating the measurement of SVs’ impact on gene expression. We anticipate Genome-Shuffle-seq will be broadly useful for the systematic exploration of the functional consequences of SVs on gene expression, chromatin landscape, and 3D nuclear architecture, while also initiating a path towards a minimal mammalian genome.
Project description:Studying the functional consequences of structural variants (SVs) in mammalian genomes is challenging because: 1) SVs arise much less commonly than single nucleotide variants or small indels; and 2) methods to generate, map and characterize SVs in model systems are underdeveloped. To address these challenges, we developed Genome-Shuffle-seq, a method that enables the multiplex generation and mapping of thousands of SVs (deletions, inversions, translocations, extrachromosomal circles) throughout mammalian genomes. We also demonstrate the co-capture of SV identity with single-cell transcriptomes, facilitating the measurement of SVs’ impact on gene expression. We anticipate Genome-Shuffle-seq will be broadly useful for the systematic exploration of the functional consequences of SVs on gene expression, chromatin landscape, and 3D nuclear architecture, while also initiating a path towards a minimal mammalian genome.
Project description:Higher order chromatin structure is important for regulation of genes by distal regulatory sequences. Structural variants that alter 3D genome organization can lead to enhancer-promoter rewiring and human disease, particularly in the context of cancer. However, only a small minority of structural variants are associated with altered gene expression and it remains unclear why certain structural variants lead to changes in distal gene expression and others do not. To address these questions, we used a combination of genomic profiling and genome engineering to identify sites of recurrent changes in 3D genome structure in cancer and determine the effects of specific rearrangements on oncogene activation. By analyzing Hi-C data from 92 cancer cell lines and patient samples, we identified loci affected by recurrent alterations to 3D genome structure, including oncogenes such as MYC, TERT, and CCND1. Using CRISPR/Cas9 genome engineering to generate de novo structural variants, we show that oncogene activity can be predicted using “Activity-by-Contact” models that consider partner region chromatin contacts and enhancer activity. However, Activity-by-Contact models are only predictive of specific subsets of genes in the genome, suggesting that different classes of genes engage in distinct modes of regulation by distal regulatory elements. These results indicate that structural variants that alter 3D genome organization are widespread in cancer genomes and begin to illustrate predictive rules for the consequences of structural variants on oncogene activation.