Comprehensive Somatic Variant Characterization at the HGSC
- Institution
- Baylor College of Medicine, TX
- Principal investigator
- Richard A Gibbs
- Funding
- $3.0M
- Duration
- 2023–2028
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Abstract
Studies of somatic mutations have so far focused on pathogenic variation, leading to cancer or severe disease. The Somatic Mosaicism Across Human Tissues (SMaHT) program will now expand knowledge of this critical class of genomic variation in normal tissues and build a comprehensive understanding of the biology of somatic variation in all contexts. The Genome Characterization Center at the Baylor College of Medicine Human Genome Sequencing Center (HGSC) will characterize variation in 750 tissue samples - 1/3 of the Program’s 15 samples from each of 150 individuals. Novel steps have been incorporated into our study design to enable comprehensive discovery of somatic mutations. Both common core assay types (WGS short-read, long read and bulk RNAseq) and two additional assays (nanoSeq and snRNAseq) that our group specializes will be used for data generation. Benchmark standards, harmonized data structures and SOPs will be created in collaboration with other Network members using established state-of-the-art methods for discovery and orthogonal approaches for technical validation. New technologies that satisfy performance criteria will be introduced into production. Statistical models will guide tissue-subsampling and sequencing strategies, set the current thresholds with further room for improvement. NanoSeq and single nuclear RNA procedures will each be modified for enhanced performance and close collaboration with investigators developing additional tools will ensure optimal discovery. Local analyses will generate lists of putative variants, with a particular focus upon characterization of long read sequence data. The latter will enable modelling of transposition events, revealed within evidence for structural variation, as well as changes in patterns of epigenetic marks. All data will be subjected to rigorous QA/QC, in collaboration with the DAC, and mirrored in the centralized data repository.
Research team
- Harsha Vardhan DoddapaneniPI
- Richard A GibbsPI
- Chenghang ZongPI
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