A long-read sequencing resource for 1000 Genomes Project samples

About This Grant

Project Summary/Abstract This project aims to generate and analyze long-read sequencing (LRS) data from 1,022 unique samples from the 1000 Genomes Project (1KGP) using both the Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) platforms. Data from 1KGP samples have been used to improve our understanding of normal patterns of human variation, but much of the structural variation (SV; insertions, deletions, inversions, and translocations) and variation in low-complexity or repetitive regions of the genome remain incompletely characterized due to the limitations of prior technologies, such as short-read sequencing. Data generated as part of this effort will include the remaining 952 singleton 1KGP samples for which LRS data have not been previously generated, 40 parents to complete parent-child trios, and 30 controls sequenced by other efforts. We will sequence 30 samples on both platforms (1,052 total samples sequenced). First, these samples will be sequenced to an average depth of coverage of >30x on either the PacBio or ONT platforms, with average read lengths >40 kbp for samples sequenced on the ONT platform. These data will be publicly released shortly after generation, validation, and QC. Second, we will aggregate and harmonize SV analyses using LRS data from this study and the 1,552 other singleton samples sequenced as part of other efforts to produce a publicly accessible resource of SVs and small variants in difficult regions of the genome that includes all 2,504 singleton samples from 1KGP to be used for clinical and basic research. This will address the technical limitations due to varying quality of data that have been generated across the cohort. Harmonized data will be released at defined intervals so that outside groups can take advantage of combined data before the completion of the project. We will continue to hold LRS consortium calls to present analysis or methods that are open to any researcher and make workflows and methods for harmonization publicly available. Third, we will develop tools and web-based resources that incorporate data generated in this study to support filtering, prioritization, and annotation of complex variants in LRS data and to allow researchers to easily interact with and explore LRS data from the 1KGP. As part of these efforts, we will explore the integration of SV data with haplotype phasing and epigenetic modifications, offering new insights into the functional impact of SVs on gene expression and regulatory mechanisms. The end product of this resource will be broadly accessible LRS data and a harmonized SV call set from all 2,504 unrelated samples and a subset of trios from the 1KGP that can be used by both researchers and clinicians to identify and further define rare pathogenic variants underlying disease. This project will utilize a key NHGRI resource, significantly enhance current reference datasets of human genetic variation, and support future research in genomics and personalized medicine.