June 1, 2021  |  

A workflow for the comprehensive detection and prioritization of variants in human genomes with PacBio HiFi reads

PacBio HiFi reads (minimum 99% accuracy, 15-25 kb read length) have emerged as a powerful data type for comprehensive variant detection in human genomes. The HiFi read length extends confident mapping and variant calling to repetitive regions of the genome that are not accessible with short reads. Read length also improves detection of structural variants (SVs), with recall exceeding that of short reads by over 30%. High read quality allows for accurate single nucleotide variant and small indel detection, with precision and recall matching that of short reads. While many tools have been developed to take advantage of these qualities of HiFi reads, there is no end-to-end workflow for the filtering and prioritization of variants uniquely detected with long reads for rare and undiagnosed disease research. We have developed a flexible, modular workflow and web portal for variant analysis from HiFi reads and applied it to a set of rare disease cases unsolved by short-read whole genome sequencing. We expect that broad application of long-read variant detection workflows will solve many more rare disease cases. We have made these tools available at https://github.com/williamrowell/pbRUGD-workflow, and we hope they serve a starting point for developing a robust analysis framework for long read variant detection for rare diseases.

April 21, 2020  |  

A robust benchmark for germline structural variant detection

New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution, and comprehensiveness. Translating these methods to routine research and clinical practice requires robust benchmark sets. We developed the first benchmark set for identification of both false negative and false positive germline SVs, which complements recent efforts emphasizing increasingly comprehensive characterization of SVs. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle (GIAB) Consortium integrated 19 sequence-resolved variant calling methods, both alignment- and de novo assembly-based, from short-, linked-, and long-read sequencing, as well as optical and electronic mapping. The final benchmark set contains 12745 isolated, sequence-resolved insertion and deletion calls =50 base pairs (bp) discovered by at least 2 technologies or 5 callsets, genotyped as heterozygous or homozygous variants by long reads. The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.66 Gbp and 9641 SVs supported by at least one diploid assembly. Support for SVs was assessed using svviz with short-, linked-, and long-read sequence data. In general, there was strong support from multiple technologies for the benchmark SVs, with 90 % of the Tier 1 SVs having support in reads from more than one technology. The Mendelian genotype error rate was 0.3 %, and genotype concordance with manual curation was >98.7 %. We demonstrate the utility of the benchmark set by showing it reliably identifies both false negatives and false positives in high-quality SV callsets from short-, linked-, and long-read sequencing and optical mapping.

April 21, 2020  |  

Multi-platform discovery of haplotype-resolved structural variation in human genomes.

The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50?bp) and 27,622 SVs (=50?bp) per genome. We also discover 156 inversions per genome and 58 of the inversions intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a three to sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The methods and the dataset presented serve as a gold standard for the scientific community allowing us to make recommendations for maximizing structural variation sensitivity for future genome sequencing studies.

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