Awardees

The Data Analysis Center (DAC) at Harvard Medical School is the central hub for collecting, processing, and sharing data and metadata from all centers across the Network. The DAC develops standardized pipelines and benchmarks for detecting somatic variants so that results are consistent across centers and sequencing platforms. Through the SMaHT Data Portal, it provides the research community with open access to these data and tools.

The New York Genome Center is one of the 5 "Genome Characterization Centers" in SMaHT. They obtain samples from the Tissue Procurement Center and perform the "core assays" (short read whole-genome sequencing and transcriptome sequencing with Illumina, long read sequencing with Oxford Nanopore). In addition, they employ a dual-strand sequencing assay from Ultima Genomics called ppmSeq (paired plus-minus sequencing). They collaborate with some of the "Tool and Technology Development" groups to sequence samples prepared with various protocols and contribute to multiple analyses in the Network to improve the characterization of somatic mosaicism.

Numerous recent studies have consistently shown that likely no two cells in the human body have the same genomes, a phenomenon called somatic mosaicism. Mosaicism can be studied using various approaches, but the study of mutations directly in the cell promises a comprehensive characterization of mosaicism in any tissue. However, all existing methods have significant limitations for studying the genome in a cell. In our project we develop and test a hybrid approach, which allows comprehensive and accurate analysis of the cell's genomes in various tissues of the human body.

Led by Dr. Sangita Choudhury at Boston Children's Hospital and Harvard Medical School, our SMaHT Technology and Tool Development project focuses on advancing highly sensitive, scalable sequencing technologies for detecting and characterizing rare somatic mutations across human tissues. We are developing Tn5-based duplex sequencing (Tn5-duplex-seq), an innovative single-molecule approach that enables accurate detection of low-frequency somatic variants while reducing sequencing costs and input DNA requirements. By integrating duplex-consensus sequencing with optimized experimental and computational workflows, our team aims to improve the accuracy, efficiency, and accessibility of somatic mutation profiling across diverse tissues and cell types. These advances will contribute to the SMaHT Network's mission of building a comprehensive atlas of human somatic mosaicism and understanding how somatic mutations arise and accumulate during development, aging, and disease.

The NYU Tools and Technology Development team is developing new DNA sequencing technology that achieves extremely high fidelity when profiling single molecules of DNA. This enables detection of DNA mutations, base pair mismatches, and damage with the goal of understanding the origins of mutations.

The UMass Chan Medical School TTD is developing new tools for identification and functional annotation of somatic variants in gene regulatory regions. We have developed a method called varCUT&Tag that enriches for regulatory regions, enabling identification of rare variants, while also allowing the functional impact of regulatory variants to be inferred. Our approach facilitates the process of screening through non-coding variants for those with potential functional consequences, which can then be prioritized for additional analyses.

The Case Western Reserve University team, led by Drs. Fulai Jin and Yan Li, develops single-cell genomic and computational tools to connect somatic mutations with their cellular context. Through SMaHT's Tool and Technology Development program, the team established a Dip-C–based approach that simultaneously profiles somatic DNA variation and three-dimensional genome organization in the same nucleus. This approach combines mutation detection, computational cell-type identification, and haplotype phasing to characterize rare mutations and chromosomal alterations within complex human tissues. Building on this work, the team continues to develop and apply these methods in human pancreatic islets to investigate how somatic mutations influence cellular fitness during aging and in diabetes, advancing SMaHT's goal of understanding the biological consequences of somatic mosaicism.