Biology subjects

Feng, W. C.

Publications and source records attributed to Feng, W. C..

3 recordsLinked to original sources

bioRxiv2025

A comprehensive view of somatic mosaicism by single-cell DNA analysis

Single-cell DNA sequencing offers a powerful means of studying somatic mosaicism but requires careful analysis to mitigate DNA amplification-related artifacts. We performed primary template-directed amplification (PTA) and sequencing of 102 nuclei from postmortem lung and colon tissues of a 74-year-old male. Single-cell mutation burdens and spectra were validated by duplex sequencing and revealed heterogeneity across organs and cells, including signatures of APOBEC activity and tobacco exposure. Cells from both tissues exhibited chromosomal aneuploidies, loss of chromosome Y, and chromosomal rearrangements including rearrangements of the T-cell receptor loci indicative of T-cells. Shared embryonic mutations between cells enabled reconstruction of cellular ancestries from the zygote, which were validated by bulk sequencing. Collectively, we demonstrate a comprehensive approach for single-cell genomics that yields an expansive view of diverse somatic mutation types from development through aging across diverse tissues--insights that are obscured in bulk sequencing and only partially captured by other single-cell methods.

genomics↗

bioRxiv2025

Comprehensive benchmarking of somatic single-nucleotide variant and indel detection at ultra-low allele fractions using short- and long-read data

Mosaic mutations in normal tissues occur at low variant allele fractions (VAFs), complicating detection. To benchmark strategies, the SMaHT Network created a cell-line mixture (1:49) and produced ultra-deep whole-genome sequencing using short and long reads (five centers, 180-500x each). We assembled a reference of 44,008 mosaic SNVs and 2,059 Indels, cross-validation between platforms to expose limits of short-read analysis. We also partitioned the genome by mappability to examine the impact of genomic context, added a negative reference set, and accounted for culture-derived mutations. When seven institutions applied eleven algorithms to mixture data, call sets were largely discordant across tools and replicates, partly reflecting stochastic presence of low-VAF mutations in biological replicants. For >2% VAF SNVs, sensitivity and precision approached [~]80% at [≥]300x, with little gain from additional sequencing. This work provides a comprehensive framework for reliable detection of low-VAF mutations in non-cancer tissues and a valuable resource for the community.

bioinformatics↗

bioRxiv2025

Multi-platform framework for mapping somatic retrotransposition in human tissues

Mobile element insertions (MEI) shape the human genome in both germline and somatic tissues. While inherited MEIs are well characterized, mapping somatic MEIs (sMEI) in non-cancer tissues remains challenging due to their low allelic fraction and repetitive nature. We established an integrative framework for sMEI analysis leveraging modern sequencing technologies and analytical innovations. We first benchmarked sMEI detection and demonstrated advantages of long-read and MEI-targeted sequencing for ultra-low-frequency events using a mixture of well-established cell lines. We then showed that haplotype phasing and donor-specific assemblies refine sMEI detection, effectively distinguishing from germline and false signals in in-silico tumor-normal mixtures. We further developed a source-tracing strategy based on internal sequence variation, expanding the catalogue of active source elements beyond traditional transduction-based methods. Applying this framework to donor tissues, we identified 18 rare somatic L1 insertions, revealing structural and source diversity. Our work provides a foundational framework and biological insight into sMEIs.

genomics↗