Biomedical subjects

Erik Garrison

Publications and source records attributed to Erik Garrison.

4 recordsLinked to original sources

PubMed2026

COSIGT: population-scalable genotyping of complex loci from low-coverage sequencing data using pangenome graphs.

Pangenome graphs capture extensive structural diversity, but resolving complex loci from shallow sequencing remains challenging, particularly when samples are of low quality such as in ancient DNA. We introduce COSIGT (COsine SImilarity-based GenoTyper), which assigns diploid genotypes by matching read-depth distributions to haplotype paths via cosine similarity. Because this metric evaluates relative coverage profiles rather than absolute read counts, COSIGT substantially outperforms existing likelihood-based tools at low coverage (1-2X). We demonstrate scalability to thousands of modern and ancient genomes, enabling robust, population-scale analyses of complex variation directly from low-coverage datasets.

Humans↗

PubMed2025

Chromosome-specific epigenetic control and transmission of ribosomal DNA arrays in Hominidae genomes.

Ribosomal RNA (rRNA) genes are organized in tandem arrays known as ribosomal DNA (rDNA) on multiple chromosomes in Hominidae genomes. We measured copy number and transcriptional activity status of rRNA gene arrays across multiple individual genomes, revealing an identifiable fingerprint of rDNA copy number and activity. In some cases, entire arrays were transcriptionally silent, characterized by high DNA methylation across the rRNA gene, inaccessible chromatin, and the absence of transcription factors and transcripts. Silent arrays showed reduced association with the nucleolus and decreased interchromosomal interactions, consistent with the model that nucleolar organizer function depends on transcriptional activity. Removing rDNA methylation activated silent arrays. Array activity status remained stable through induced pluripotent stem cell reprogramming and differentiation into cerebral and intestinal organoids. Haplotype tracing in two unrelated family trios showed paternal transmission of silent arrays. We propose that the epigenetic state buffers rRNA gene dosage, specifies nucleolar organizer function, and can propagate transgenerationally.

Epigenesis, Genetic↗

PubMed2025

A complete diploid human genome benchmark for personalized genomics.

Human genome resequencing typically involves mapping reads to a reference genome to call variants; however, this approach suffers from both technical and reference biases, leaving many duplicated and structurally polymorphic regions of the genome unmapped. Consequently, existing variant benchmarks, generated by the same methods, fail to assess these complex regions. To address this limitation, we present a telomere-to-telomere genome benchmark that achieves near-perfect accuracy (i.e. no detectable errors) across 99.4% of the complete, diploid HG002 genome. This benchmark adds 701.4 Mb of autosomal sequence and both sex chromosomes (216.8 Mb), totaling 15.3% of the genome that was absent from prior benchmarks. We also provide a diploid annotation of genes, transposable elements, segmental duplications, and satellite repeats, including 39,144 protein-coding genes across both haplotypes. To facilitate application of the benchmark, we developed tools for measuring the accuracy of sequencing reads, phased variant call sets, and genome assemblies against a diploid reference. Genome-wide analyses show that state-of-the-art de novo assembly methods resolve 2-7% more sequence and outperform variant calling accuracy by an order of magnitude, yielding just one error per 100 kb across 99.9% of the benchmark regions. Adoption of genome-based benchmarking is expected to accelerate the development of cost-effective methods for complete genome sequencing, expanding the reach of genomic medicine to the entire genome and enabling a new era of personalized genomics.

Journal Article↗

PubMed2025

wgatools: an ultrafast toolkit for manipulating whole-genome alignments.

SUMMARY: With the rapid development of long-read sequencing technologies, the era of individual complete genomes is approaching. We have developed wgatools, a cross-platform, ultrafast toolkit that supports a range of whole-genome alignment formats, offering practical tools for conversion, processing, evaluation, and visualization of alignments, thereby facilitating population-level genome analysis and advancing functional and evolutionary genomics. AVAILABILITY AND IMPLEMENTATION: wgatools supports diverse formats and can process, filter, and statistically evaluate alignments, perform alignment-based variant calling, and visualize alignments both locally and genome-wide. Built with Rust for efficiency and safe memory usage, it ensures fast performance and can handle large datasets consisting of hundreds of genomes. wgatools is published as free software under the MIT open-source license, and its source code is freely available at https://github.com/wjwei-handsome/wgatools and https://zenodo.org/records/14882797.

Software↗